Noname manuscript No.

(will be inserted by the editor)

In Memoriam Douglas N. Walton: The influence of Doug
Walton on AI and Law
Katie Atkinson · Trevor Bench-Capon ·Floris Bex · Thomas Gordon · Henry
Prakken · Giovanni Sartor · Bart Verheij

the date of receipt and acceptance should be inserted later

Abstract Doug Walton, who died in January 2020, was a prolific author whose

work in informal logic and argumentation had a profound influence on Artificial
Intelligence, including Artificial Intelligence and Law. He was also very interested
in interdisciplinary work, and a frequent and generous collaborator. In this paper seven leading researchers in AI and Law, all past programme chairs of theInternational Conference on AI and Law who have worked with him, describe his
influence on their work.

1 Introduction

On January 3, 2020, we lost a good friend and colleague, Douglas Walton. He
was 77 and is survived by his wife, Karen.
Doug served for many years as a member of the editorial board of this journal.
He was one of the leading experts in the field of argumentation and highly prolific.
Katie Atkinson
Department of Computer Science. University of Liverpool.
Trevor Bench-Capon
Department of Computer Science. University of Liverpool.
Floris Bex
Department of Information and Computing Sciences, Utrecht University and Institute for Law,
Technology and Society, Tilburg University.
Thomas F. Gordon
Falkensee, Germany, http://www.tfgordon.de
Henry Prakken
Department of Information and Computing Sciences, Utrecht University and Faculty of Law,
University of Groningen.
Giovanni Sartor
University of Bologna, and European University Institute, San Domenico di Fiesole.
Bart Verheij
Department of Artificial Intelligence, Bernoulli Institute of Mathematics, Computer Scienceand Artificial Intelligence, University of Groningen.

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Katie Atkinson et al.

He authored or co-authored more than 50 books and published more than 400
peer reviewed journal articles and conference papers. And his work was not only
voluminous but also highly influential, as attested by his high citation indexes,
one of the highest in our community.
Doug earned his PhD in philosophy at the University of Toronto, Canada, in1972. After completing his PhD he was awarded a professorship in the philosophy
department at the University of Winnipeg, starting in 1972. He became a full
professor there in 1982 and carried on in this capacity until his retirement in 2008.
But research and writing remained Doug’s passion and he gave no thought to theidea of actually retiring. He moved to the University of Windsor, Canada, where
he held the Assumption Chair of Argumentation Studies until 2014, and thencontinued on at Windsor as a Distinguished Research Fellow of the Centre for
Research in Reasoning, Argumentation, and Rhetoric (CRRAR) until his death.
During his long career he travelled extensively, including several longer visits asa fellow or visiting professor, at the Institute for Advanced Study in the Humanities and Social Sciences in the Netherlands (1987-88 and 1989-90), the Oregon
Humanities Center (1997), Northwestern University (1999), the University of Arizona (2001), the University of Lugano (2007) and the Department of Law at theEuropean University Institute, Florence (2011).
One of the hallmark’s of Doug’s career was his enthusiasm for interdisciplinary
research, in particular in collaboration with computer scientists and lawyers working in the fields of Artificial Intelligence and Law as well as, somewhat later,
Computational Models of Argument. This collaboration began in the late 1990s,
presumably as a result of his participation at the first Formal and Applied Practical Reasoning (FAPR) conference [46], which was held in Bonn, Germany, in 1996.
The FAPR conference brought together researchers working on practical reasoning
and other forms of argument from both philosophy and artificial intelligence. Doug
was already 56 at the time and well established in philosophy as a leading expert
in the field of argumentation. At this stage in his life and career he had no needto take on the challenges of entering a new, if related, field, especially a highly
technical one such as artificial intelligence. But he not only persisted, overcoming
challenges, but succeeded in making a large impact, significantly influencing thework of several of the leading researchers in these fields.
Of his over 50 books on argumentation, several of them were directly relevant for the field of Artificial Intelligence and Law, including Legal Argumentationand Evidence [150], Argumentation Methods for Artificial Intelligence and Law [151],
Character Evidence, An Abductive Theory [152], Witness Testimony Evidence: Argumentation, Artificial Intelligence and Law [155], Burden of Proof, Presumption andArgumentation [157], Argument Evaluation and Evidence [157], and the Handbook of
Legal Reasoning and Argumentation [39, co-editor]. Doug also published fourteen
papers in the Artificial Intelligence and Law journal.
But Doug is probably best known for his original, ground-breaking work on the
topics of argumentation schemes and dialogue types, as expressed for example inhis books Commitment in Dialogue [166, with Erik Krabbe], Argumentation Schemes
for Presumptive Reasoning [146], Argumentation Schemes [167, with Chris Reed andFabrizio Macagno], The New Dialectic [148] and Dialog Theory for Critical Argumentation [154]. His work on argumentation schemes and dialog types is summarized
in the next section of this article. And for a good overview of his perspective on

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

3argumentation, his textbook Fundamentals of Critical Argumentation [153] is highly
recommended.
This paper commemorates Doug Walton’s impact on the field of Artificial Intelligence Law, with contributions from a number of people who have worked withhim, explaining how Doug’s work has influenced them and, in return, how workin the field of AI and Law has influenced Doug’s further work on argumentation.
We will always remember Doug fondly. He will be sorely missed.

2 Selected Overview of Walton’s Work

Doug was, of course, not a computer scientist but a philosopher and an informal
logician. Although he collaborated with computer scientists and published in computer science venues, his work is very much in his own tradition. None the lessseveral aspects of his work, although motivated by concerns from his own discipline, proved inspirational to computer scientists. Two topics in particular have
had a wide ranging and lasting influence. Both addressed problems that computerscientists were struggling with when they discovered his work. His work on dialogue types in [166] and [148] helped to solve problems in the development ofinter-agent communications, and his work on argumentation schemes [146] and[167] was taken up at a time when the interest of Artificial Intelligence had been
turned towards argumentation by Dung’s seminal paper [42]. Dung’s theory of
abstract argumentation needed to be complemented by a way of doing structured
argumentation, and one way of doing this was provided by argumentation schemes.
In the remainder of this section we will summarise these two important contributions.

2.1 Dialogue Types
One aspect of Doug’s work which has had a considerable impact on Computer
Science is his notion of dialogue types. This idea was introduced in [145], developed
and organised in joint work with Eric Krabbe [166], and further expounded in[148]. The impact of this work was heightened by the context in which it was
introduced.
In the mid-90s multi-agent systems were very much a hot topic of research [124].
The basic idea was that systems could be realised as groups of communicating
agents and
Implementations of systems based on distributed agent architectures require an agent communications language that has a clearly defined semantics. Without one, neither agents nor developers can be sure what anotheragent’s commitment to perform a task means (to name just one speechact). [123].
As that quote suggests, a central source of inspiration was John Searle’s Speech Acts[119]. The underlying idea here was that people communicate through performativeutterances, utterances intended to perform actions such as asking and telling, andthat these could be defined in terms of preconditions (sometimes called felicity
conditions ) for their use, and the post-conditions that result from their use. Thus

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Katie Atkinson et al.

we saw the development of several agent communication languages intended toprovide agents with a repertoire of speech acts, the best known of which was
KQML [44]. A semantics for KQML was given in [76]. A typical example from
KQML is tell(A,B,X), where A tells B that X.
tell(A,B,X)

1. Preconditions for A: bel(A,X) and know(A, want(B,know(B,bel(A,X))))
2. Preconditions for B: intend(B,know(B, beI(A,X)))
3. Postcondition for A: know(A,know(B,bel(A,X)))
4. Postcondition for B: know(B, bel(A,X))
5. Completion: know(B, bel(A,X))
Two features here are problematic: first that there is much appeal to internal
states of the agent (believe, know, want, intend etc.), some of which are nested.
Some of them cannot possibly be determined by the agent: for example A is required to know that B wants to know. These private semantics are unverifiable,
and thus it is not possible to know whether the act can be performed. Partly as aresult there are sincerity conditions built in to the speech acts: one cannot lie using the KQML tell. This might be possible in a closed system where all agents are
known to be co-operative, but cannot easily be extended to open systems where
there is always a danger of encountering malicious agents. The alternative is asemantics based not on mental states, but on social commitments [121]The second problem is that the definition gives a very restricted view of tell,whereas in practice the speech act is rather flexible, capable of different uses indifferent contexts. For example, I can tell people things that I know they do notwant to know, and (since sincerity conditions do not apply in the real world), I
will have no idea whether they will believe me or not.
Both of these problems are addressed by Doug’s notion of dialogue types. As
the title of [166], Commitment in Dialogue, indicates, the central idea is that agents
enter into public commitments when engaged in dialogue. An agent who asserts a
proposition is committed to its truth for the purposes of that dialogue, irrespectiveof whether the agent really believes it. These public commitments can then form
the basis of preconditions for the various speech acts, without the need to speculate
on mental states. In this way both participants can be observed to be obeying theprotocols. The notion of commitment was already familiar from dialogue games
such as Mackenzie’s DC [85] and, in AI and Law, Tom Gordon’s Pleadings Game[48], but Doug’s account put the idea on firm philosophical foundations.
The idea of different dialogue types enabled the speech acts to be considered ina context, so that the meaning could be understood in the context in which it was
performed, thus allowing for the essential pragmatic aspects to be captured as wellas the semantic aspects. This idea was recognised in the agent community in theconversation classes of COOL [12], whereby specific tasks were defined as a set ofspeech acts specific to that task. This made the speech acts rather ad hoc, peculiar
to quite specific tasks. In [14] three different tasks in which tell might be used
are specified, with the conditions specified to capture the pragmatic differences
between the tasks. But whereas KQML was too general, defining the speech acts
relative to single tasks was too specific. The notion of dialogue classes in [166]offered a sensible middle way, and one soundly based on philosophy and informal
logic.
The basic tenet of [166] is that

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

5propositional commitments depend on a context of dialogue. There aremany different normative models of a dialogue, each of which has its own
distinctive goals and rules. Accordingly it is possible to distinguish several important characteristic types of dialogue. Each type of dialogue has
different kinds of rules for the management of commitments.
Six main dialogue types were identified in [166]: persuasion, negotiation, inquiry, deliberation, information seeking and eristic. Mixed dialogues were also
possible. The possibility of shifting from one dialogue type to another needs to berecognised: failing to notice such a shift so that the participants are unaware of
the type of the dialogue in which they are engaged will lead to misunderstandings.
Dialogue types can be defined by specifying:– The initial situation;– The overall (collective) goal;– The individual aims of the participants (which may differ or even conflict),

A summary of these defining characteristics for the six dialogue types is shownin Table 1. For each of these dialogue types it is possible to identify a set ofspeech acts, enabling the dialogue type to be realised in an agent system. Examples
are: [99] (persuasion), [176] (negotiation), [37] (inquiry) and [10] (deliberation andpersuasion). Apart from the eristic type, there are examples for all the other types.
These six types, however, are not intended to be exhaustive and exploration of
additional types has proved fruitful: for example examination dialogues [43] andadjudication dialogues [100].
Doug’s work on dialogue types in an excellent illustration of the importanceof interdisciplinary perspectives: work produced to satisfy concerns arising frominformal logic proved immensely useful in solving problems arising in inter-agent
communication, notably the avoidance of private semantics and the incorporationof context and the pragmatic considerations arising from context in the specification of speech acts for agents.

Table 1 Types of Dialogue as summarised in [2]Type

Initial Situation

Persuasion

Conflicting points ofview

Negotiation

Conflict of interests
and need for cooperation
General ignorance

Inquiry
Infoseeking

Personal ignorance

Deliberation

Need for action

Eristic Dialogue

Conflict and antagonism

Main Goal of Dialogue
Resolution of suchconflicts by verbal
means
Making a deal

Participants’ Aims

Growth of knowledge
and agreement
Spreading knowledge
and revealing positions
Reach a decision

Find a proof or destroy one
Gain, pass on, showorhide
personal
knowledge
Influence the outcome
Strike the other party
and win in the eyes of
onlookers

Reaching an accommodation in a relationship

Persuade the other(s)Get the best out of itfor oneself

6Katie Atkinson et al.

2.2 Argumentation Schemes
Argumentation schemes have a long history, as set out in [81]. Classical versionsof argumentation schemes can be found in Aristotle and Cicero. Moving on to theMiddle Ages we have Boethius and Abelard. Moving on to modern times, schemes
were used by Perelman [91], Toulmin [128] and the Pragma-Dialectics school [131].
That of Toulmin had a particular impact on AI and Law e.g. [80], [86], [13]. Doug
produced a distinctive account of argumentation schemes in [146] and [167]. It
is on Doug’s understanding of argumentation schemes that we will focus in thispaper.
Argumentation schemes are contextual forms of argument, where the conclusion of the argument is made more plausible or persuasive if the premises of theargument are believed or accepted to be true. Schemes come with a set of criticalquestions suggesting ways to make other arguments which can undermine or attack the argument. Using schemes, multiple arguments pro and con a claim canbe constructed, which may need to be balanced to reach a decision about whether
or not to accept the claim. In Doug’s own words:
Several distinct forms of argument . . . are not deductive or inductive
in nature. These arguments are presumptive and defeasible . . . Each of theforms of argument described in this chapter is used as a presumptive argument in a dialogue that carries a weight of plausibility. If the respondentaccepts the premises, then that gives him a good reason to also accept theconclusion. But it does not mean that the respondent should accept theconclusion uncritically. Matching each form of argument is a set of appropriate critical questions to ask. In a given case, there may be a balanceof considerations to take into account. There may be some arguments infavour of the conclusion and some against it. These forms of argument are
called argumentation schemes, and they represent many common types ofargumentation that are familiar in everyday conversations. They need tobe evaluated in the context of dialogue. They are used to shift a burdenof proof to one side or the other in a dialogue and need to be evaluateddifferently at different stages of a dialogue. . . . [153, p. 84]
Here is Doug’s standard example of an argumentation scheme [153, pp. 87–88], for arguments from expert witness testimony, illustrating the three parts ofschemes (premises, conclusion and critical questions):
major premise: Source E is an expert in the subject domain D containing proposition A.
minor premise: E asserts that proposition A is true.
conclusion: A may be plausibly be taken to be true.
The critical questions of the expert witness testimony scheme are:expertise question. How credible is E as an expert source?
field question. Is E an expert in the field that A is in?
opinion question. What did E assert that implies A?
trustworthiness question. Is E personally reliable as a source?
consistency question. Is A consistent with what other experts assert?
backup evidence question. Is E ’s assertion based on evidence?

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

7

Now we can see why schemes are contextual, unlike the inference rules of someaxiomatization of classical logic. The premises, conclusion and critical questions ofargumentation schemes are not entirely abstract, but make use of predicates fromsome domain of discourse, such as, in this example, ‘expert’, ‘credible’, ‘field’, and‘reliable’. By they are also not entirely concrete. The premises, conclusion andcritical questions of a scheme have schema variables (E, D and A in this example)
which must be instantiated with constants denoting individuals when applying thescheme to construct an argument.
So far we have only discussed the form and the parts of argumentation schemes.
Let us now turn to their purposes and how they are intended to be used in dialogues. They have multiple uses. Their first use, the one Doug tends to emphasise
most, is for critically evaluating arguments which have been put forward in a dialogue. The basic idea is try to match the argument to one of the schemes in a large
catalogue of schemes in order to, first, check that the scheme has been correctly
applied and then, second, if one accepts the premises but is not yet persuaded thatthe conclusion is true, to use the critical questions associated with the scheme totry to defeat or at least weaken the argument.
Another use of schemes, which Doug has also investigated [162, 164, 165], is forconstructing or, as Doug prefers to say, ‘inventing’ arguments to put forward ina dialogue. Here, a participant in the dialogue can refer to a catalogue of argumentation schemes to try to find some which may be applicable and useful for
supporting or attacking some claim of the dialogue.
A third use of argumentation schemes is to allocate the burden of proof in
dialogues. With regard to burden of proof, critical questions are of two kinds:assumptions. Some critical questions, once they have been asked, create a burdenof proof on the party who put forward the argument to provide an argument
supporting the questioned premise. That is, the premise is assumed to be true
unless it is questioned, after which it is no longer assumed but must be supported by further arguments and evidence. An example of this kind of criticalquestion is the expertise question of the expert witness testimony scheme. The
witness may be assumed to be an expert unless his expertise is questioned, atwhich point the party who made the argument must provide evidence of theexpertise of the witness.
exceptions. The other kind of critical question expresses an exception. Here theburden of proof is placed on the respondent, the party challenging the argument by asking the critical question, to provide an argument proving theexception holds, thereby undercutting the first argument. The trustworthinesscritical question of the expert witness testimony scheme is of this kind. If the
respondent questions the trustworthiness of the witness, he or she must provide
an argument proving the witness is not trustworthy.
When used to regulate the burden of proof in dialogues, argumentation schemes
become part of the protocol or procedural rules of the particular dialogue type orprocedure. There are many types of dialogues and such protocols or procedural
rules are norms for regulating and conducting dialogs of the given type, in orderpromote the values and goals of the dialogue type. Since argumentation schemes
are context-dependent, particular schemes can be developed for specific, domaindependent dialogue types. For example, in the law, specific legal norms can be

8Katie Atkinson et al.

interpreted as argumentation schemes for allocating the burden of proof in eachlegal domain, such as criminal or contract law.
As can be seen from the use of argumentation schemes to regulate the burden of proof in dialogues, argumentation schemes can serve a normative function.
Schemes, however, can also be studied from an empirical perspective. One canidentify and classify common patterns and forms of argumentation in different
contexts, such as everyday conversation, academic discourses or in the law. This issomething that Doug has done extensively and is one of his main contributions to
the topic of argumentation schemes [146, 167]. His latest compendium, from 2008,
written with Chris Reed and Fabrizio Macagno [167] is a collection of 96 common
argumentation schemes.
Let us end this brief overview of Doug’s work on argumentation schemes with a
discussion about some related work, to help to put his contribution into a broader
context. Doug does not claim to have invented the idea of an argumentation
scheme. Forms of argument have long been recognized and studied in philosophy, going back to at least Aristotle’s study of the topics [122]. In [151, p. 10],
Doug cites [67, 130, 73] as more immediate sources.
Toulmin’s analysis of the form of argument [128] is related but quite different
from the argumentation schemes developed by Doug. Toulmin’s analysis was at
a different level of abstraction. Toulmin identified parts of an argument (e.g. datum, warrant, claim, and backing) and showed how such arguments are used indialogues, but he did not study extensively more specific forms of argument, suchas argument from expert witness testimony.
Prior to Doug’s work on argumentation schemes, a much greater emphasis
was placed in philosophy on studying fallacies [66], that is, bad or misleading
forms of argument. Argumentation schemes complement fallacies, by describing
and analysing good forms of argument. To some extent argumentation schemes
may be seen as challenging a basic premise of fallacies, if one takes the position
that only arguments in which the conclusion is necessarily true are not fallacious.
From the perspective of argumentation schemes, ‘fallacious’ arguments may be
weak or defeasible arguments, but not necessarily improper or useless. Moreover,which forms of arguments to admit for use in a particular dialogue type is, fromthe perspective of argumentation schemes, a normative issue to be addressed when
deciding which procedure and schemes are best suited for achieving the goals of
the particular dialogue type.
Argumentation schemes also need to be contrasted with the inference rules of
the axiomatization of some logic, such as modus ponens in an axiomatization ofclassical logic. Although they have syntactical similarities, they are quite different
semantically and pragmatically. A collection of argumentation schemes can not,by itself, formalize or axiomatize a logic, because argumentation schemes are expressed informally, in natural language, and are not sufficiently abstract, as they
contain domain-specific terms and predicates. Although it is possible to formalize
argumentation schemes [163], it is then the schemes which are being formalized,
rather than being used as tools to formalize a logic.
This is not the place to try to assess Doug’s contributions to the study ofargumentation schemes, to try to clarify exactly which parts of his work on argumentation schemes was original or can be attributed to prior work from othersources. Doug’s work on argumentation schemes was important and influential not
only because of its originality, but also because of his dedication and tireless efforts

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

9to explain, illustrate and apply the theory of argumentation schemes in various
domains, through extensive interdisciplinary collaboration.

3 Katie Atkinson: Persuasive Argument in Practical Reasoning

Doug’s influence on my own research career took effect right at the very start of my
PhD studies. I commenced my PhD with a clear idea that I wanted to investigate
argumentation and negotiation through formal dialogue models, but with little
certainty as to the precise research question which I would address through thesestudies. I read Doug’s book, The New Dialectic [148], early on in my first year of
PhD study and this provided me with a sharper focus for a particular subject ofstudy. In that book, Doug sets out a precise characterisation of the different typesof dialogue, which were identified in an earlier book (Commitment in Dialog [166])
that he co-authored with Erik Krabbe. As described in the previous section, eachof the dialogue types identified is given a characterisation in terms of the starting
position, overall dialogue goal and individual participants’ goals over what theywish to achieve through the dialogue. The persuasion dialogue type became thefocus of my PhD work since this encompasses the type of adversarial arguments I
wished to study.
As well as studying the modelling of formal dialogues, which aligned with theinterests and expertise of one of my PhD supervisors, Peter McBurney, I was also
studying the recent work of my other supervisor, Trevor Bench-Capon. Trevor
had recently published his seminal paper on value-based argumentation [15] andat that time we were discussing the application of value-based reasoning in law. In
doing so, we were considering reasoning problems that were focussed on justifying
the outcome of actions in reasoning about legal cases, e.g. find for plaintiff, orfind for defendant. We were considering these problems from the viewpoint of
persuasive dialogue, but found that a nuance within the usual characterisation of
persuasion was lacking: we needed our formal model of persuasion to distinguishbetween persuasion about what to believe and persuasion about what to do. Whilst
persuasion over beliefs was undoubtedly an important topic to model, Dungianabstract argumentation frameworks [42], provided sufficient tools for tackling thisproblem for our purposes. Conversely, reasoning about what to do, had not yet
been articulated in a sufficiently expressive form to enable value-based reasoning
to be captured to model the domain applications we were considering, mainly inlaw. This is where Doug’s argumentation schemes came into play.
Reasoning about what to do – herein referred to as practical reasoning – canbe regarded as a species of presumptive argument that gives a reason for performing an action. However, this presumption can be challenged and withdrawn.
Subjecting an argument to appropriate challenges is how we hoped to identify andconsider any alternatives that require contemplation, and ultimately determine thebest choice for the individual(s) making the decision, in the particular context. To
cite a simple example based on the practical syllogism [72]:I’m to be in London at 4.15.
If I catch the 2.30, I’ll be in London at 4.15.
So, I’ll catch the 2.30.

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Katie Atkinson et al.

Challenging this argument:– There may be alternative ways of achieving the goal.
– Performing an action typically excludes the performance of other actions, whichmight have other more desirable results.
– Performing an action make have further unconsidered, undesirable consequences,that may be sufficiently bad to lead us to abandon the goal.
These considerations are addressed within Doug’s account of presumptive reasoning, as given in [146], which captures such reasoning in terms of argumentation
schemes and critical questions. The idea is that an argumentation scheme gives apresumption in favour of its conclusion. Whether this presumption stands or falls
depends on satisfactory answers being given to the critical questions associatedwith the scheme. In [146] Doug gave two schemes for practical reasoning:
1. The necessary condition scheme:
G is a goal for a
Doing A is necessary for a to carry out G
Therefore a ought to do A.
2. The sufficient condition scheme:
G is a goal for a
Doing A is sufficient for a to carry out G
Therefore a ought to do A.
Associated with these schemes are four critical questions:– CQ1: Are there alternative ways of realising G?
– CQ2: Is it possible to do A?
– CQ3: Does a have goals other than G which should be taken into account?
– CQ4: Are there other consequences of doing A which should be taken into

account?
In [11] these schemes were taken as a starting point and expanded to covera wider, more fine-grained range of relevant considerations covering consequencesof actions, achievement of goals and promotion of social values by execution ofactions. This expanded scheme for practical reasoning is as follows:
In the circumstances R
we should perform action A
to achieve new circumstances S
which will realise some goal G
which will promote some value V.
The expanded argumentation scheme gives rise to an expanded set of criticalquestions as follows:– CQ1: Are the believed circumstances true?
– CQ2: Assuming the circumstances, does the action have the stated conse-

quences?
– CQ3: Assuming the circumstances and that the action has the stated conse-

quences, will the action bring about the desired goal?

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

11– CQ4: Does the goal realise the value stated?
– CQ5: Are there alternative ways of realising the same consequences?
– CQ6: Are there alternative ways of realising the same goal?
– CQ7: Are there alternative ways of promoting the same value?
– CQ8: Does doing the action have a side effect which demotes the value?
– CQ9: Does doing the action have a side effect which demotes some other value?
– CQ10: Does doing the action promote some other value?
– CQ11: Does doing the action preclude some other action which would promote

some other value?
– CQ12: Are the circumstances as described possible?
– CQ13: Is the action possible?
– CQ14: Are the consequences as described possible?
– CQ15: Can the desired goal be realised?
– CQ16: Is the value indeed a legitimate value?

This natural language description of the scheme and critical questions provides
a template for instantiation to enable proposals for what to do to be made andcritiqued in a wide range of domains, including the legal domain where an earlyexample in [63]1 set out to apply this to case-based reasoning. The next stepundertaken was to automate this reasoning to turn it into an account that could
be used by autonomous agents.
To give both the argumentation scheme and the critical questions precise interpretations, a semantic structure was used as the basis for their definition; thisstructure is an Action-based Alternating Transition System [129]. An AATS comprises states with actions labelling transitions between states, and these actions
have pre-conditions that must be met to enable the action’s execution. Statescomprise sets of propositions, so goal states can be identified by propositions that
hold true in a given state. The original specification of an AATS did not accountfor the notion of values, so to allow for this and enable specification of the practical reasoning argumentation scheme, the definition of an AATS was extended
to associate the promotion and demotion of values with state transitions. As wellproviding the required formalisation, the AATS enables consideration to be givenof a society of agents and their differing choices such that the reasoning can capture decision making of an individual agent whilst also taking into account what
other agents in the environment might choose to do. In an AATS this is captured
through the notion of joint actions2 .
In [4] it was shown how the practical reasoning argumentation and its critical questions could be given a precise, rigorous definition in terms of an AATS
to enable this account of practical reasoning to be used in agent systems. That
account shows, through a detailed worked example, how to instantiate the formal
version of the scheme and critical questions to enable the generation of a set ofarguments for and against a proposal for action. Once generated, these arguments
then need to be evaluated to determine, from the competing set within the debate,
which arguments are the winning ones and why. At our disposal for this task werevalue-based argumentation frameworks (VAFs), as had already been defined by
Trevor Bench-Capon [15].
1This paper is one of two I published in 2003 under my prior surname of Greenwood.
In an AATS joint actions are simply actions performed simultaneously by different agents:
no idea of cooperation or coordination is intended.
2

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Katie Atkinson et al.

The nodes in a VAF correspond to the arguments generated through instantiation of the practical reasoning argumentation scheme and instantiation of its
associated critical questions. The attack relation is determined by instantiationsof critical questions that subject the original proposal for action to scrutiny. Once
the VAF representing the debate is determined, the VAF is evaluated to determine
which of the competing proposals for action is the winning one. This is decided byapplying the audience’s preference ordering over values, since multiple instantiations of the practical reasoning argument scheme will yield different proposals foraction, promoting different values. A full example showing how to generate andevaluate practical reasoning arguments using AATSs and VAFs is given in [20].
The formalisation described above enables the informal version of the practicalreasoning argumentation scheme to be turned into a computational account. A
longer commentary on this exercise is provided by Trevor and I in the paper that
we contributed to Doug’s Festschrift in 2010 [19]. However, the move from theinformal to the formal account as described above overlooks the dialogical natureof argumentation schemes that has been a focus of Doug’s work.
In my own work, I have together with other collaborators developed computational accounts of various types of dialogue from the Walton and Krabbe typology,
including persuasion [2], deliberation [126] and inquiry [36]. Over a number of years
I had discussions with colleagues in the computational argumentation community
about the nuanced characterisation of persuasion over action and deliberation dialogues. In 2013 Doug, Trevor and I tackled this topic to provide an account that
illuminated the distinctive features of persuasion and deliberation dialogues [10].
The motivation for the paper goes back to some of Doug’s earlier insights regarding
the importance of recognising the distinctions between dialogue types, since participants in both types of dialogues will have different aims, which in turn affects
whether a successful outcome can be reached.
Persuasion over action and deliberation dialogues are typically conducted byexchanging arguments for and against particular options whereby the moves ofthe dialogue are designed to facilitate such exchanges. Our account showed how
the pre- and post-conditions for the use of particular moves in the dialogues arevery different depending upon whether they are used as part of a persuasion overaction dialogue or a deliberation dialogue. We drew out the distinctions throughan example (based on a dialogue about choosing a restaurant to eat at) presented
as a logic program in order to give a clear characterisation of the two types of
dialogues and enable them to be implemented within systems requiring automatedcommunication. In 2019 this line of work was taken forward in a student projectat the University of Liverpool, published in [74], which presented an implemented
tool that captures the distinctive features of each of the two dialogue types, tomake plain their differences and to validate the speech acts for use in practicalscenarios. The starting point for that paper can clearly be traced back to the
dialogue typology presented in [166]; the relevance of Doug’s work for dialogue
models for AI is still being shown 25 years after the typology was first published.
From a personal perspective, I have had the honour of discussing Doug’s workand my own research with him at length on two particular occasions (in addition to
the many enjoyable meetings we had at academic conferences). The first occasion
was during my PhD studies where I was invited to be the designated respondent
for a talk that Doug was delivering at the Norms, Reasoning and Knowledge inTechnology workshop, held in Boxmeer, The Netherlands in June 2005. The paper

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

13that Doug presented was titled Evaluating and Implementing Practical Reasoning and
I was delighted to be the respondent for his talk to speak about implementation ofsystems based on informal logic models of practical reasoning, and in particular thedevelopment of such tools for e-democracy applications [8] which were of interest
to the legal field. Doug was very welcoming to junior researchers and generous
with the time he gave listening to and talking through old and new ideas onargumentation. The second occasion I refer to was the viva voce examination for
my PhD degree in 2005 at which Doug served as the external examiner. I felt very
lucky to have had the opportunity to discuss my research in depth with such anesteemed contributor to the field of argumentation theory who influenced my own
work and whose legacy can be seen in a wide range of work on argumentation in
AI and Law.

4 Trevor Bench-Capon; Driving Dialogues with Critical Questions

Before taking up computer science I studied philosophy and worked in a policy branch of the Civil Service. Thus I have always been attracted by argument[16]. Initially I used argument to explore notions of open texture [27]. The notion of argument there was simply the proof trace of a logic program. This is arather impoverished form of argument, missing such important features as the useof enthymemes, the treatment of exceptions, and the reason why the conclusion
follows from the premises. All of these features can be found in Toulmin’s argument scheme [128]. Accordingly I, like several others (e.g. [80] and [86]), adopted
that scheme for the explanation of logic programs [23]. Toulmin’s scheme was well
suited to presentation of arguments, but generation was done using the underlying
logic program. I also used Toulmin’s scheme to drive dialogues. The idea was thatthe various dialogue moves would navigate Toulmin’s structure. This was used
for explanation in [22] and as the basis of a persuasion dialogue in [13]. In these
dialogues, the computer would generate the argument as in [23], and then reveal
the scheme in response to questions from the user. By the late 90s, I felt that I
had gone as far as I could with Toulmin’s scheme, and began to take more interestin abstract argumentation [42], especially as extended to support reasoning withsocial values [15] and [26].
It was against this background that I encountered Doug Walton’s seminal bookon argumentation schemes [146]. From this I learnt three important lessons:– there is not just one argument scheme: there are many;– there is not a fixed set of argument schemes: one can develop one’s own forparticular purposes;– and, most significant of the three, argument schemes are associated with char-acteristic critical questions which provide ways to attack arguments based on
the schemes.
Also around this time I encountered a second of Doug’s works, which developed the notion of dialogue types [166]. Together these two works reawakened myinterest in dialogues and argumentation schemes, and have formed the basis of agreat deal of my subsequent work.

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Katie Atkinson et al.

In 2002 I had begun to supervise a PhD student3 , Katie Atkinson. Her thesis was to become What Should We Do? [2]. We explored the topic of practicalreasoning through the use of a particular dialogue type taken from [166], persuasion dialogues, and by the development of a particular argument scheme forvalue based practical reasoning and its associated critical questions, inspired by
two schemes from [146], together with Perelman’s notion of an audience [91] as
expressed computationally in [15]. The first appearance of our new scheme was in[7]. The key difference between the scheme inspired by Doug and my previous useof the Toulmin scheme was that Doug’s schemes enabled the generation of competing arguments through the instantiation of the scheme and its critical questions.
These arguments could then be organised into and evaluated using value based
argumentation frameworks [4]. I will say no more about these aspects as they havealready been discussed by Katie in the previous section.
I shall, however, discuss the influence of critical questions on dialogue design.
Katie did implement a dialogue system (PARMA) in [2], but here I shall focus
my work with another PhD student4 , Maya Wardeh [171], whose primary aim was
to explore persuasion dialogues based on the discovery of association rules. For
this purpose we first developed a dialogue protocol (PADUA). This protocol was
entirely based on an argumentation scheme and its critical questions. These werefirst described in [172]. We called the scheme Argument from Proposed Rule withfour premises:
1. Data Premise: There is a set of examples D pertaining to the domain.
2. Rule Premise: From D a Rule R can be mined with a level of confidence greaterthan some threshold T. R has antecedents A and a conclusion which includes
membership of class C.
3. Example Premise: Example E satisfies A.
4. Conclusion: E is a C because A.
This can be subject to a number of critical questions:
1. Can the case be distinguished from the proposed rule?
2. Does the rule have unwanted consequences?
3. Can the rule be strengthened by adding additional antecedents?
4. Can the rule be improved by withdrawing consequences?
5. Is there a stronger counter rule?
There were six legal dialogue moves based on instantiating the scheme and thecritical questions. The inspiration of Doug’s [146] conception of argumentation
schemes in is evident in this scheme and its critical questions. Maya’s work gavea convincing demonstration of the utility of argumentation schemes and criticalquestions as the basis for dialogue design. The dialogues are a great improvementon the Toulmin based dialogues such as [13], since they offer a genuinely adversarial dialogue (the two players are mining different data sets), rather than thepresentation of a computation which has been done prior to the dialogue. PADUA(and its development PISA which supported more than two players) was, by its
ability to challenge the arguments, able to refine the rules to achieve a high levelof accuracy (e.g. around 95% using a commonly used AI and Law dataset [173]).
3
4

Co-supervised with Peter McBurney.
Co-supervised with Frans Coenen.

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

15This idea of using an argumentation scheme and critical questions to specify adialogue was also used in the e-participation system PARMENIDES [8], initiallydeveloped by Katie Atkinson in [2], which was based on the practical reasoningargumentation scheme and a selection of its critical questions. After further refinement by Katie and her student Dan Cartwright [40], this work was subsequently
developed into the Structured Consultation Tool (SCT) of the IMPACT project5
The SCT enabled a member of the public to receive a detailed, tailored, justification of a policy proposal, or for the member of the public to present a proposal
for critique [179]. The fullest account of the SCT is in [21].
As well as driving dialogues, it is also possible to use argument schemes tocapture reasoning methods [102]. That is, a whole method for a particular kindof reasoning can be expressed as a cascade of argumentation schemes and theircritical questions. My attempts to do this centred around the method for reasoning
with precedent cases that is found in CATO [1], which has proved quite central
to AI and Law accounts of case based reasoning [18]. The first attempt was madein [177] in which the various argument moves of [1] such as citing, distinguishing and downplaying were expressed in a set of argument schemes. Thus use ofargument schemes permitted a precise characterisation of the actions and a helpful visualisation of the reasoning. The schemes were applied to Popov v Hayashi
in [17]. These schemes were further refined in [178]. Schemes to enable reasoning
with values were given in [25] and schemes using dimensions rather than simple
factors were presented in [9]. A consolidation of this line of work was made in[111]. A similar approach to capture practical reasoning as a set of argumentation
schemes was made in [5], and to reasoning about the actions of other agents in[6]. In all these cases I found argumentation schemes a very fruitful way to think
about these problems, and to express the reasoning involved.
The growing importance of argumentation in AI has been a story of this century. But whereas in general AI abstract argumentation has had the bigger impact, AI and Law has always seen the structure of arguments as of key importance.
Doug’s conception of argumentation schemes combines two important aspects oflegal argument: the inherent defeasibility, and the adversarial nature of the process. In consequence, Doug’s work has provided a lens through which to view
legal reasoning, and he has had a profound influence on the way the subject hasdeveloped over the last two decades.

5 Floris Bex; from Arguments to Stories and Explanations

I first came into contact with Doug’s work as an undergraduate in 2003. I wasdoing a research internship with Henry Prakken, comparing three formalisms forreasoning with evidence in the law: Pollock-style argumentation [92, 108], abductive model-based reasoning [79, 70] and Bayesian networks [69]. The comparison
was done by modelling a Wigmore chart [174] of the well-known Sacco and Vanzetti
case [71] in all the three formalisms. The argumentation-based modelling of thecase was subsequently used in a paper ([30] see Section 7.2) making Doug and me
5 Integrated Method for Policy making using Argument modelling and Computer assisted
Text analysis. An FP7 project, Grant Agreement No. 247228.

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Katie Atkinson et al.

co-authors - though we wouldn’t meet in person until 20076 . By that time I had
already started my PhD, also with Henry Prakken, on formal models of stories andarguments in reasoning with evidence and facts in legal cases. During this PhD,
I developed the so-called hybrid theory of stories and arguments [28], a mixture ofargument-based and story-based reasoning.
In argument-based reasoning, arguments are constructed by performing consecutive reasoning steps from evidence to conclusion. Each of these reasoning steps has
an underlying evidential generalisation of the form “e is evidence for p”. Reasoning with arguments is dialectical because not only arguments for a conclusion but
also counterarguments are considered. Story-based reasoning involves constructing
stories about what (might have) happened in a case to explain the evidence. Reasoning with stories can be characterised as causal reasoning: the relations between
the events in a story and between the story and the evidence can be expressed
as causal generalisations “c is a cause for e”. This approach is also dialectical: an
explanation is defeasible, that is, it holds tentatively by placing a burden on an
opponent to critically question it and to offer a possible alternative explanation.
In the hybrid approach, stories and arguments are combined for reasoning
about the facts of a case. Stories can be used as hypothetical scenarios about “whathappened” in the case, to explain the main observations. Arguments can then be
used to argue about these stories. For example, arguments based on evidence canbe used to support or attack stories (or each other). Figure 1 shows an exampleof two stories explaining a crash in the Anderson v. Griffin case (397 F.3d 515),
taken from [33]. Here, there are two stories about why the crash occurred. Whileboth stories agree on the fact that the driveshaft broke, the plaintiff (p) argued
that the truck dealer did not repair the driveshaft, whereas the defendant argued
there was debris on the road, which struck the driveshaft, causing it to break.

6 Either at that year’s ICAIL conference in Stanford or the visualising evidence symposium
organised by Peter Tillers in New York.

Truck driver’s records.

Plaintiff’s expert.

The truck dealer did not repair
the driveshaft (p).
There was debris on
the road (d).

Testimony of
witnesses.

The driveshaft
broke (p,d).

Debris struck thedriveshaft (d).

Testimony ofdefendant’s expert.

The crashoccurred (p,d).

Driveshaft rotates athigh speed.

Testimony ofplaintiff’s expert.

Fig. 1 Two stories with supporting and attacking evidential arguments, taken from [33].
Arrows with an open arrowhead denote causal links (stories), arrows with a closed arrowhead
denote evidential links (arguments) and an arrow with a rounded (dot) arrowhead denotes anattack of an argument on a story.

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

17

5.1 Schemes and Critical Questions in the Hybrid Theory
When reasoning with the evidence and facts in a case, we use a large amount ofknowledge about the world we live in. This knowledge is not based on the specificevidence in the case, but rather it is the common sense knowledge we often takefor granted, for example, ‘experts normally speak the truth’, or ‘Murders often
involve a weapon’. Such pieces of common sense knowledge, or generalisations,have varying degrees of reliability – some of it may be based on false beliefs orstereotypes, and for every generalisation there is a situation in which it does not
hold7 . It is therefore important that we critically analyse and question the common
sense knowledge we use when reasoning with evidence. Here, the link with Doug’s
argumentation schemes and their critical questions becomes clear.
With respect to argumentation schemes, we can see that many argumentation
schemes are evidential generalisations ([150], see also Section 7.2). Take, for example, the argumentation scheme for expert evidence (Section 2.2): the fact that‘expert E asserts that proposition A is true’ is evidence for ‘A is true’. Criticalquestions point to possible counterarguments – a negative answer to the question‘Is E an expert in the field that A is in?’ can be seen as an exception to thegeneralisation that experts usually can be believed.
Stories are also based on general schemes or story schemes (also called scripts[118]), which represent general knowledge of stories, how certain situations normally develop. For example, the well-known ‘restaurant-script’ contains information about the standard sequence(s) of events that take place when somebody
goes to dine in a restaurant. Story schemes mention not only a sequence of events,
but also other information important in a story of that particular type. Take, forexample, the story scheme for ‘murder’ [28]:1. Anomaly that the scheme explains: person y is dead.
2. Central action of the scheme: person x kills person y .
3. Other relevant information: the motive m, the time of the killing t, the placeof the killing p, the weapon w.
4. Pattern of actions: person x has a motive m to kill person y -— person x kills
person y (at time t) (at place p) (with weapon w) -— person y is dead.
5. More specific kinds of murder: assassination (e.g. liquidation), felony murder(e.g. robbery murder), killing of one’s spouse.
In addition to a pattern of actions, this scheme also contains other information,such as what the central action is and which other, more specific schemes might beapplicable. Other story schemes are more abstract: for example, Pennington andHastie [90] mention an abstract episode scheme for intentional actions, a patternof the form motive – goal – action – consequences.
Story schemes are important when reasoning about the evidence and facts incriminal cases: they are used to explain events, as they connect an event with an
explanation that has been used to explain that sort of event before. When facedwith some initial evidence, people draw on a range of standard scenarios (i.e. story
schemes). For example, when a body is found in a house, the initial schemes police
investigators use are ‘murder’, ‘accident’ and ‘suicide’.
7

Since this generalisation is true, it is itself the situation in which it does not hold.

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Katie Atkinson et al.

In addition to aiding explanatory inference, story schemes can also be used to
critically analyse existing stories and, in particular, the coherence of stories. For
example, if a story does not fit a particular scheme because some of the elementsof the scheme are not in the story (for example, no mention is made of the motive
in a murder story or the causal link between the murderous action and the victim’s
death is not made clear), the story’s coherence diminishes. Like arguments, stories in evidential reasoning are dialectical, and critical questions associated with astory scheme can point to counterarguments. Note, for example, the similarity between the elements of Pennington and Hastie’s intentional action scheme (motive,
goal, action, consequences) and the argumentation scheme for practical reasoning(discussed in Section 3). This means that the critical questions of the scheme forpractical reasoning can used to question and analyse motives and actions of characters in stories [29]. For example, for a murder story we can ask the following
questions.
1. Did person x have the opportunity to kill person y ?
2. Is motive m a legitimate motive for killing?
3. Would x have a reason not to kill y ?
Critical questions can also be used to analyse more complex reasoning. In
fact, Bart Verheij and I considered critical questions not just for individual argumentation or story schemes but also for the process of reasoning with stories
and arguments as a whole [31]. Thus, we proposed three types of critical questions
that are useful when reasoning with evidence: (i) critical questions associated withthe argumentation schemes, which can be used to analyse arguments based on evidence; (ii) critical questions associated with the story schemes, with which the
hypothetical stories about the facts may be analysed; and (iii) critical questions
for a hybrid argumentative-narrative case analysis, which may be used to analyse
the case as-a-whole, that is, the combination of stories and arguments supportingor attacking these stories. Some examples of the latter as are follows.
1. Are the facts of the case made sufficiently explicit in a story? Is the story sufficiently coherent? Are there elements missing? Are there implausible elementsin the story?
2. Is the story sufficiently supported by evidence? Is the support that the evidence
gives to the story sufficiently relevant and strong?

5.2 Burdens and standards of proof for the Hybrid Theory
Even though we had been co-authors since 2003, it would not be until after my PhD
when we would first actively work together as co-authors [32]. In 2010 I visited
Doug in Windsor, and I vividly remember the walks along the waterfront andour conversations. We talked about argumentation, explanation and the burdenof proof, about which Doug had already published quite extensively, also withsome of the other authors of this paper [106, 60]. We set to work looking if someof Doug’s earlier ideas could be applied to the hybrid theory, which after a Jurix
article [32] would culminate in a paper in Law, Probability and Risk [33].
In their argumentative account of burdens of proof, Prakken and Sartor [110]define three kinds of burden of proof in terms of claims and the arguments forIn Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

19these claims. We applied their definitions to stories and arguments for and against
these stories. Having the burden of persuasion for a story S means that at theend of the trial S should be accepted as the correct explanation of what happenedin the case – in a civil case such as Anderson v. Griffin (Figure 1) the burden of
persuasion lies with the plaintiff. The tactical burden shifts throughout the case,and depends on which story that meets the standard of proof is currently thebest. In the Anderson v. Griffin case, after the plaintiff has made his initial case
based on the records, the tactical burden shifts to the defendant to come up withan alternative explanation. The burden of production may be met by providing
evidence that directly or indirectly supports the story on which the burden rests. In
the Anderson v. Griffin case, after the defendant has produced his story about thedebris, the burden of producing the evidence for his story lies with the defendant.
Note that the notion of a burden of proof presupposes certain standards of
proof. Here, we followed Doug’s earlier work with Tom Gordon [60]. A story S
meets the scintilla of evidence (SE) standard if there is at least one justified argument based on evidence supporting S . A story S meets the preponderance ofevidence (PE) standard if it meets the SE standard and it is better than each alternative story S 0 – that is, S is either supported by more evidence or contradictedby less evidence than S 0 . This is the standard for civil cases such as Anderson v.
Griffin, and the plaintiff’s story seems to meet it – it has two supporting arguments and while the defendant’s story also has two supporting arguments, it also
has an attacking argument. For clear and convincing evidence (CCE), a story S
should be good in itself as well as much better than each competing story S 0 . In
order to be good, S should be supported by many arguments and contradicted by
few arguments. In order to be much better than any alternative S 0 , S should have
either significantly more arguments supporting it, or significantly less arguments
contradicting it. Finally, a story meets the beyond a reasonable doubt (BRD) standard if it meets the CCE standard and each competing story is very weak, so weak
as to be highly implausible.

5.3 Argumentation and Explanation in Dialogue
During my visit to Windsor, Doug and I also started talking about the differences,similarities and interplay between argumentation and explanation8 . The point isthat, in a dialogue, argumentation and explanation are not always easily distinguishable. Logic textbooks (e.g. [68]) offer a pragmatic test to determine whether apassage expresses an argument or an explanation, where the focus is on the proposition or event that is to be explained or proved. If this proposition is not subject
to doubt (e.g. it is generally accepted as true), the passage should be taken as an
explanation. If it is subject to doubt, that is, if it is unsettled whether it is trueor not, then the passage should be taken as an argument. The difficulty with thisis that it is often hard to determine whether a proposition is “generally accepted
as true”, and that argument and explanation can only be properly distinguishedby looking at the dialogical context of reasoning, that is, the original intention of
the speaker (to argue or explain) but also at the utterance that was replied to andthe beliefs and intentions of the audience.
8 This subject has now again become a hot topic in the context of explainable AI, see e.g.
[87].

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Katie Atkinson et al.

If it is so difficult to distinguish argument and explanation, one could ask ‘whybother?’. In our paper [34], Doug provided a compelling reason. Circular arguments, where the conclusion of one argument is the premise of another argument
and vice versa (i.e. p therefore q; q therefore p ), can be viewed as an instance of the
fallacy of ‘begging the question’. However, in the case of explanation, circularity
need not be a problem – in fact, there are many vicious (causal) circles that clearly
explain why events happened as they did. For example, in the Anderson v. Griffincase (Figure 1), it is conceivable that the debris striking the underside of the carcaused new debris to fall on the road, which would then again strike the car.
As Doug and I argued, in a dialogue we should be clear if we are offering or
asking for an explanation or an argument, as they are evaluated differently. Hence,in any formal dialogue game we need to have different speech acts for asking forand offering arguments and explanations.

5.4 Concluding: the dialectical stance
Doug’s ideas on argumentation schemes as representing general knowledge about
dialectical reasoning had a profound impact on the hybrid theory. Particularly theidea of critical questions, which can and should be asked when reasoning withevidence in different ways, has influenced the hybrid theory, lifting it (particularly
more informal versions of it) from a ‘mere’ knowledge representation theory toa more normative, dialectical theory that can be used to critically analyse one’s
reasoning. In this sense, Doug’s work has taught me the true meaning of what, inwhat proved to be out last collaboration [35], we called the dialectical stance 9 .

6 Thomas Gordon: Supporting argumentation with the Carneades system

When I entered the field of AI and Law in 1982, shortly after finishing law school,
I worked on the topic of legal expert systems in the legal informatics group headed
by Herbert Fiedler at the German Society for Mathematics and Computer Science(GMD) in Sankt Augustin. As a law student at UC Davis, in California, I had
constructed a small expert system for an area of US securities law in an independent study project, using the E-MYCIN rule-based system10 in collaboration with
Stanford University. In my efforts to model legal norms using rule-based systems
and the Prolog logic programming language, I began to appreciate that norms are
typically defeasible, subject to exceptions, and became interested in nonmonotonic
logics as a way to model such defeasible norms. However, as a result of also taking
a deeper interest in work in legal philosophy on legal reasoning and argumentation,
I soon came to view nonmonotonic logics, or indeed any kind of logic, as being too
limited to fully capture legal reasoning and argumentation. The process not only
applies rules deductively to facts to draw (defeasible) inferences, but also involves
9 A stance is the level of abstraction on which decisions or behaviour are judged. Cf. Dennett’s intentional stance [41], which views the behaviour of an entity in terms of the mental
properties (intentions) of the entity. The dialectical stance views our reasoning behaviour interms of arguments and counterarguments.
10 E-MYCIN, or essential MYCIN, was a version of the pioneering expert system MYCIN[120] with the domain knowledge removed to be replaced by the user’s own knowledge base.

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

21

constructing these rules and facts by interpreting legal source texts and evidence,in a goal-directed way during legal procedures, which are multi-party argumentative dialogues. The parties in these dialogues take turns making speech acts, forexample by raising issues, making claims, and constructing and putting forward
arguments to support these claims. From a higher-level perspective, the goal ofeach party is to construct a theory of the law and the facts of the case which ismore coherent and persuasive than the theory put forward by the opposing party,
because of the reasons put forward in the arguments supporting and attacking thecompeting theories.
As a result of these insights, I began to view this procedural, dialogical approach to modeling legal reasoning and argumentation as an application of what
I called “computational dialectics”. Together with Ron Loui, I organized a workshop on computational dialectics as part of the AAAI conference in Seattle in 1994.
Gerhard Brewka and I organized a second workshop on computational dialectics
as part of the Formal and Applied Practical Reasoning (FAPR) conference, which
took place in Bonn, Germany, in 1996.
It was at the FAPR conference that I first encountered Doug Walton. Douggave one of the invited talks at the conference. And he took part in our workshop
on computational dialectics. I remember him sitting quietly in the back of theroom, listening attentively. I remember feeling honored that he would take aninterest in our workshop. I am not longer sure, but I do not recall that we actually
talked to each other on this occasion. So it may be that we did not really get toknow each other more personally until a couple of years later.
In 1998 or 99, about two years after the FAPR conference, Doug sent me a
copy of his latest book, The New Dialectic. I was extremely surprised and honored
that he closed the book with some very kind comments about my PhD thesis,
The Pleadings Game, which takes the dialectical perspective on legal reasoning andargumentation outlined above. I must have contacted him to thank him, and thiswas when we became better acquainted with each other.
However it would be a few years before, in 2005, we began our collaboration inearnest and wrote a paper together [161]. From that point on we published at least
one paper together almost every year, except 2008 and 2013, up to and including
2018, about the time I retired. Altogether we published 19 papers together, overa period of 13 years. A selection of these papers is summarized below.
Our first joint paper was Critical Questions in Computational Models of Legal
Argument [161] in 2005. It compared my first attempt to model the critical questions of Doug’s theory of argumentation schemes [50] with the approach proposed
by Verheij [137]. Both of us modelled critical questions as additional premises ofarguments, which could then be used to attack the argument. The unique featureof my approach was that it included a computational model of various proof standards, similar to my prior work on Zeno [54], and allowed a different standard to
be assigned each issue, that is to each contested premise, independently. Anotheradvantage of my approach was that it distinguished different types of critical questions (called exceptions and presumptions) and assigned the burden of proof to theparties depending on the type. This allowed one to choose between the “shifting
burden” and the “backing evidence” theories of critical questions [160], for eachcritical question.
The following year, in 2006, we published our first paper on the Carneades
Argumentation Framework [58] along with a paper showing how to use Carneades

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Katie Atkinson et al.

to model the arguments in the Pierson v Post legal case [57]. Carneades grewout of the work discussed above [161]. In the early version of [58] it provided aformal model of the structure of a set of interconnected arguments, called “argument graphs” and of argument evaluation, using models of proof standards andburden of proof to determine which statements (propositions) are acceptable. This
formal model was implemented in a software system, also called Carneades, forhelping users to construct, evaluate and visualize argument graphs. The visualization method was similar to the one used in Araucaria [114], but with extensions
for distinguishing different kinds of premises (ordinary, presumptions, exceptions).
Soon thereafter Doug began using and promoting this and later versions of theCarneades argument diagramming method in his books and other publications. In
2007 a journal version of this work was published in Artificial Intelligence journal[55]. Henry Prakken joined us as a co-author and helped us in particular with
proving some properties of the formal model.
In 2009, Doug and I contributed a chapter on formal models of proof burdens
and standards to the book Argumentation in Artificial Intelligence edited by Rahwan and Simari [60]. While the chapter was mainly a survey and analysis of prior
work, it also included an updated version of the Carneades formal model of structured argument and evaluation in [55], extended with formal models of dialogues,
audiences, and the different types of burdens identified by Prakken and Sartor in[110]: the burdens of claiming, questioning, argument production, persuasion, andthe tactical burden of proof.
Also in 2009, Doug and I published our first paper together on how to integrate heterogeneous computational models of various argumentation schemes intoa hybrid system for constructing and evaluating (legal) arguments [59]. The basic
idea was to view argumentation schemes as abstract data types with methods forconstructing arguments, where all such data types satisfy a common protocol, sothat they can be used together to construct arguments graphs consisting of manyarguments fitting different argumentation schemes. The argument graphs werethen evaluated using the methods developed previously for Carneades, discussed
above. We illustrated our approach with computational models of legal argumentation schemes for arguments from ontologies, rules, cases and evidence. This work
was intended to realize the claim I made in my 2007 ICAIL keynote address, thatthe diverse forms of argument identified and modelled in the field of AI and Law
could be subsumed under the concept of argumentation schemes and integrated
into a common framework for legal reasoning based on argumentation. [51]. The
computational models were implemented in the version of Carneades developed in
the European ESTRELLA project (IST-4-027655).
In 2012, Doug and I contributed an article to a special issue of this journal, AI
and Law, about different approaches to modelling the arguments in the Popov v
Hayashi case, edited by Katie Atkinson [3], in which we modelled the argumentsof the case using Carneades [61], using the same approach as we had used in ourreconstruction of the arguments in Pierson v Post in [57]. The argument diagramsin the article were generated with a new, interactive argument diagramming application for Carneades developed by Matthias Grabmair in a Google Summer ofCode project.
Also in 2012 Doug and I published an article in a philosophy journal about how
a software tool such as Carneades can be used to help people to apply argumentation schemes to construct new arguments or, as Doug liked to say, to “invent”

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

23arguments [162]. This is a good example of several articles that Doug publishedin philosophy conferences and journals, sometimes with me as co-author, about
how artificial intelligence methods and tools in general, and Carneades in particular, can be useful for assisting people to apply theories of argumentation fromphilosophy to argue better in practice. Doug served as an influential ambassador
between the philosophy and artificial intelligence communities. Another example
is [170], with Chris Tindale, where we used Carneades to reconstruct several arguments from ancient Greece philosophers, in particular the famous argument about
whether an object was a rope or snake from Carneades, the philosopher, which
had motivated us to name our system Carneades after him.
But perhaps the most significant example was published in 2015 in Informal Logic, entitled paradoxically and hopefully provocatively Formalizing Informal
Logic [163]. The field of informal logic was founded in the 1950s at a time whenformal logic was synonymous with first-order predicate logic. Our aim was to showthat newer formal models of reasoning and argumentation from the field of artificial intelligence, such as Carneades, can overcome the reservations philosophers in
the 50s had about the limitations of formal methods for modeling real-life argumentation, and using these models as a foundation for practically useful softwaretools. We did this by showing how Carneades can successfully handle the ten basic characteristics, or requirements, of informal logic in the relevant philosophy
literature.
During the period from 2016 to 2018 Doug and I published a series of papers
on the latest and presumably final version of Carneades. The first, Formalizing
Balancing Arguments, was presented at the Computational Models of Argument(COMMA 2016) conference [62]. The paper presented a major improvement to theCarneades formal model of structured argument which allowed, for the first time,arguments to be weakened or, somewhat counterintuitively perhaps, strengthened,
if a premise fails, rather that defeating the argument entirely. This enabled argument accrual to be handled, meeting all the requirements for accrual identified by
Prakken [98] but in a computationally tractable way, without causing an exponential blowup in the number of arguments. It also fixed a limitation of the original
version of the formal model of Carneades, by removing the restriction to acyclic
argument graphs. This new version handles cycles using fixed-point semantics ina way similar to and inspired by Dung Abstract Argumentation Frameworks [42],but in a direct way, without mapping structured arguments to abstract arguments,
unlike ASPIC+ [101]. The formal model was fully implemented in Version 4 of theCarneades argumentation system, for grounded semantics. The main theorem of
our COMMA paper, about the monotonicity of the characteristic function, wasleft as a conjecture. The proof was provided later in [52]. However, unfortunately,
Henry Prakken discovered a minor error in the proof via a counterexample [104],due to the definition of proof standards being unnecessarily broad and abstract.
The error can be easily fixed by restricting the definition of proof standards to ones
which are are commonly used in practice, such as the small number of legal proof
standards provided by the implementation of the Carneades system. However thisadmittedly remains to be formally proven, and it is hoped that some ambitious
doctoral student will take on this task some day.
My final paper with Doug was published in Argument and Computation in 2018,
along with my colleague at Fraunhofer, Horst Friederich [53]. In this paper we presented a programming language for argumentation schemes, based on Constraint

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Handling Rules [45], and validated the language by showing how twenty of Doug’s
most important argumentation schemes (as selected by Doug) can be represented
in the language and used to automatically generate or ‘invent’ arguments froma set of assumptions. (Moreover, in the meantime, Başak Kurtuldu has used thelanguage to represent many other of Doug’s argumentation schemes, as part ofher PhD thesis, summarized in [75].) The generated arguments are represented
using the latest version of the Carneades model of structured argument, and canthen be evaluated by this model, for example with its support for cumulative arguments. Recall that in our previous work on representing argumentation schemes[59], discussed above, we provided only a framework for integrating heterogeneous
implementations of specific schemes. This work goes beyond this prior work byproviding a very expressive, rule-based language for representing and implementing a wide range of argumentation schemes in a high-level, declarative fashion.
Others have used various rule-based languages to represent some argumentation
schemes, such as Verheij with DefLog [137], but none of these languages wereexpressive enough to handle many of Doug’s argumentation schemes, including
his leading examples of argumentation schemes, such as the scheme for argumentsfrom witness testimony, due to their lack of sufficient support for variables ranging
over propositions.
Perhaps this was a fitting last paper for us to write together. With it, Doug andI achieved the goal of formalizing all of the main features of his theory of the structure of argument, argument evaluation in dialogs, and of argumentation schemes,
with support for representing a broad range of schemes in a high-level language,
including two kinds of critical questions, automatically generating arguments fromthese schemes, and evaluating the arguments with support for distributing the burden of proof, multiple proof standards, cumulative arguments, argument accrual,
cyclic argument graphs, and generating visualizations of argument graphs in argument diagrams of the kind common in philosophy.11 Perhaps I should qualify thisclaim by saying that we achieved this goal to our mutual satisfaction. I have no
doubt that others will find ways to take this work forward and to improve upon
it in many ways. And perhaps some of our colleagues have already done so.
Let me close this section by reflecting a bit on why Doug and I enjoyed collaborating so extensively for such a long period of time. It was very easy for us
to work together. Aside from Doug being so likeable, modest, curious and open to
new ideas, I think it helped that we each had our own field of expertise. In our
relationship, Doug was the philosopher and the expert on argumentation, while I
was the computer scientist, software engineer and the one more experienced withthe technical details of artificial intelligence. I viewed myself as the software engineer trying to build models and systems which meet the requirements identified
by Doug in his theory of argumentation. I was always convinced that Doug’s approach to argumentation, with his theory of argumentation schemes and dialog
types, was very useful for the kinds of application scenarios that interested me inthe legal domain, which require quite a number of different kinds of schemes to be
applied together dialogically in legal procedures. I focused my energies on trying
to make Doug’s theory computational.
11 The source code of all versions of the Carneades software is available on Github at https://github.com/carneades.

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If I have one regret, it is that we did not find time to work more together on
the topic of formally modelling legal dialogs, which had been the focus of my PhD
thesis [49]. We had this topic on our joint research agenda, but sadly life is short.

7 Henry Prakken: Argumentation schemes and burdens of proof

My interest in argumentation mainly stems from my interest in AI and Law. Since
lawyers argue all the time, any study of how legal reasoning and decision making
can be modelled or supported by AI tools will sooner or later have to deal withargumentation. Originally I saw the formal and computational modelling of legal
argument as applying nonmonotonic logic. When I entered academia as a PhD
student in 1988, nonmonotonic logic was a trendy topic in AI, just eight years after the famous special issue of Artificial Intelligence Journal on the topic [38], andits relevance for legal reasoning seemed obvious. Although I was fascinated by the
fashionable nonmonotonic logics of those days, like default logic and circumscription, I felt that something was missing for legal applications. It was especially thework in AI and Law on legal argument by Gardner [47] and Rissland and Ashley[115] that made me aware that the notion of an argument should be central. Other
early sources of inspiration were general AI work by Poole [95] and Loui [78] (Iwas not yet aware then of the seminal work of Pollock in [92]). I designed my firstargument-based nonmonotonic logic in 1990, published as [96] (although in that
paper I did not use the term ‘argument’ but ‘proof set’). Also in my work with
Giovanni Sartor between 1995 and 1997 I mainly thought of formal argumentation
systems as a kind of nonmonotonic logic, this time based on Dung’s now famous abstract account of argumentation that he had just introduced in [42], and assumingthat arguments are created by chaining domain-specific rules (legal, commonsenseor otherwise) into inference trees. It was not until 2000, when I was a participant at the Bonskeid Symposium on Argument and Computation in the Scottish
mountains, that I became familiar with Doug Walton’s work. At this Symposium,organised by Tim Norman and Chris Reed, researchers from various formal andinformal fields met in an informal setting. Doug was among the other participants.
Various interdisciplinary collaborations resulted from this event, partly reported
in [113].

7.1 Walton’s influence on my work: general remarks
Doug Walton’s work influenced me in two ways. First, I began to see the potentialof an argumentation-scheme approach to the problem of finding the rules withwhich arguments are constructed (another source of inspiration here was John
Pollock’s account of the role of defeasible reasons in cognition [92, 94]). Second,
I became interested in dialogue models of argumentation (although here I was
more directly inspired by AI and Law work on modelling legal procedure). Below
I discuss both topics in separate subsections. But before that I should mention
that I deviated from Doug’s views on these topics in one important respect. Doug
did not see these topics as separate. He regarded argumentation schemes as essentially dialogical devices, determining dialectical obligations and burdens of proof

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(see e.g. the introduction of [146]). Using this account, a procedure for evaluating arguments constructed with argumentation schemes should take the form ofa set of dialogue rules. I instead argued in my paper for the 2010 Festschrift for
Doug [102] that argumentation schemes are essentially logical constructs, so thata procedure for evaluating arguments primarily takes the form of a logic. (In Section 9 Bart Verheij mentions that he followed a similar approach with his DefLog
system.) More specifically, I argued that most (though not all) argumentation
schemes discussed by Doug can be seen as defeasible inference rules and that theircritical questions can be seen as pointers to counterarguments, so that the logic
governing the use of argumentation schemes should be a logic for defeasible argumentation. The dialogical role of argumentation schemes can then be modelledby embedding such a logic in a system for dialogue, so that in the end argument
evaluation with argumentation schemes is a combination of logical and dialogical aspects. More specifically (see also [97]), the dialogue protocol determines therelevant arguments, counterarguments and defeat relations at each stage of the
dialogue. At each such stage the argumentation logic then determines the logicaljustification status of these arguments, after which the burden of proof shifts tothe losing side to make herself win at a new dialogue stage, and so on. Thus thejustification status of an argument depends on both logic and dialogue.

7.2 Argumentation schemes
Since I did not see how the simple rule-based approach of [107, 108] could accountfor argumentation schemes, I looked for a different formal approach. Since I saw aparallel between the notion of an argumentation scheme and Pollock’s notion of a
defeasible reason, I initially adopted a simplified version of his formalism from [93,94], noting that many of Doug’s critical questions to argumentation schemes could
be modelled as pointers to rebutting or undercutting defeaters. See e.g. [30, 98].
The first two of these papers actually contain the claim that Pollock’s work on defeasible reasons is an example of Doug’s argumentation-scheme approach. I don’t
think that Doug (a co-author of these papers) agreed with this, but he generously
allowed me to include this claim12 . In [30] we then semiformally sketched Pollock’s
way of defining arguments and his two kinds of attack, and then also semi-formallyremarked that this account could be embedded in Dung’s abstract approach. We
then continued to propose a list of argumentation schemes for evidential reasoning, some coming from Pollock’s work on defeasible reasons (perception, memory,the statistical syllogism, induction, temporal persistence) and some coming fromDoug’s work on argumentation schemes (general knowledge, expert testimony, witness testimony).
12 As an anecdote, on several occasions I tried to convince Doug that his notion of argumentation scheme was similar to Pollock’s notion of a defeasible reason. Doug was never convinced.
I later realised that this was since he saw argumentation schemes not as inference rules but
as dialogical devices. In fact, Doug once told me that he and his wife had visited Pollock in
Arizona. When I asked him whether they had talked about the relation between argumentation
schemes and defeasible reasons, Doug answered that not a single word had been exchanged
about this.

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Later I changed from a Pollock-style formalism to the ASPIC + framework [101,88, 89], which originated from the EU-funded ASPIC project13 , running from 2004
to 200714 . One aim in the ASPIC project was to consolidate the then state-of-theart in formal argumentation logics. To this end, we combined Vreeswijk’s [142,143] very elegant definition of an argument with Pollock’s distinction between
rebutting and undercutting attack (and we added premise attack or ‘undermining
attack’)15 . We then incorporated the notion of a preference relation on the setof arguments to determine which attacks succeed as defeats, resulting in a setof arguments and a defeat relation. This allowed us to use Dung’s semantics for
abstract argumentation frameworks to evaluate the arguments.
Several publications since 2010 show how reasoning with argumentation schemes
can be modelled in the ASPIC + framework, by regarding the schemes as defeasible
inference rules and the critical questions as pointers to (rebutting, undercuttingor undermining) attacks. For instance, in [88] Sanjay Modgil and I showed how
a combination of Pollock’s defeasible reasons for perception and Doug’s schemefrom the position to know can be formalised in ASPIC + . In [111] I, with Adam
Wyner, Trevor Bench-Capon and Katie Atkinson, modelled schemes for case-based
legal reasoning in ASPIC + . Moreover, in [24] Trevor, Wietske Visser and I usedvariants of Doug’s argumentation schemes from good and bad consequences toformalise two-phase democratic deliberation, and in [103] I used similar schemesin formalising debates about law-making proposals as practical reasoning. Basedon this work I still believe that the view of argumentation schemes as primarily
logical devices is a fruitful one. However, Doug was certainly right that there is adialogical side to the evaluation of arguments. To this I now turn.

7.3 Dialogue systems
The influence of Doug’s ideas on my work on argumentation dialogues was initiallymore indirect, coming through AI and Law work on modelling legal procedure with
dialogue games for argumentation [48, 64, 77]. This work was in turn inspired bya body of work in argumentation theory on so-called ‘formal dialectics’ (a termcoined by Hamblin [66]), to which Doug had made important contributions (e.g.
[175, 166]). A more direct influence came through my collaboration with Doug andChris Reed in 2004 and 2005 [105, 106]. In those days Doug thought a lot about
the problem whether asking a critical question always shifts the burden of proof
in persuasion dialogues. He realised that sometimes just asking a critical questionof an argumentation scheme is not enough to make the argument ‘default’ but
something more is needed. Once argumentation schemes are seen as defeasible
13 The ASPIC project was funded under FP6-IST, Grant agreement ID: 002307. Details canbe found at https://cordis.europa.eu/project/id/002307 (last accessed May 2020).
14 I also briefly collaborated with Walton and Tom Gordon on the Carneades framework[56], which essentially was Tom’s brainchild influenced by Doug’s philosophy, as described in
Section 6. My contributions to Carneades were modest: I mainly helped with some technicalissues. Tom very generously rewarded me with co-authorship.
15 As a historical aside, it was not us from Utrecht (Martin Caminada, Gerard Vreeswijk
and myself) but the people from IRIT in Toulouse (Leila Amgoud, Claudette Cayrol andMarie-Christine Lagasquie-Schiex) who initially proposed to use Vreeswijk’s definition of anargument and to combine it with Pollock’s distinction between rebutting and undercutting
attacks.

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inference rules and their use is embedded in dialogue systems as sketched above,a natural solution to Doug’s problem becomes available. When critical questions
point at rebutting or undercutting counterarguments, then simply asking them is
not enough to shift the dialogical burden of proof to the other side, since the ideaof defeasible reasoning is that the absence of such counterarguments is presumed.
So to shift the burden of proof, a counterargument must be provided. For instance,
when an argument from expert opinion is offered, it is not enough to ask whether
the person who is claimed to be an expert is biased, since in the absence of evidence
to the contrary, experts are presumed to be not biased. Instead, when a criticalquestion asks whether a premise of an argument instantiating a scheme is true,
then the premise must be further supported, so simply asking whether it is true
shifts the burden of proof. For example, that someone who is claimed to be an
expert on a given issue really is an expert cannot simply be presumed but must beargued for when challenged. In my papers with Doug and Chris Reed on dialogue
we modelled this approach by, at each stage of a dialogue, excluding the argumentswith challenged premises from the set of arguments to which the argumentation
logic is applied at that stage (an idea originally from [97]).
There is a technical subtlety here. In some (uses of) argumentation logics theabsence of an exception is made explicit as a special type of premise (for instance,the ‘assumptions’ of assumption-based argumentation [127], which can also be
included in ASPIC + [101]). In that case there are no undercutting counterarguments and whether a critical question about a premise shifts the burden of proof
depends on whether the premise is an assumption or not. Only if it is not, does
asking whether it is true shift the burden of proof. Despite this technical difference between various (uses of) argumentation logics, the general story is the same:
logically speaking some things can be presumed in the absence of evidence to thecontrary, while other things cannot; only in the latter case does asking whether thething is true shift the burden of proof. See also the distinction between assumptions
and exceptions made above in Section 2.1.
One point made in [105, 106] is that whether something can be presumed or
not is often a domain-specific issue, which can itself become the subject of debate.
One example is legal procedure, where the distribution of the burden of proof
over the parties can become the subject of debate. Accordingly, Doug, Chris andI proposed a dialogue system in which a challenge of a premises ϕ of an argument
can be answered with ‘you have the burden of proving ¬ϕ because . . . ”. Sucha move makes the dialogue shift to an embedded burden-of-proof dialogue, theoutcome of which determines whether the challenge of ϕ has any dialogical effect.
These ideas were formalised within my general approach to formalising persuasion
dialogues proposed in [97].
After our two joint publications, Doug, Chris and I did not further pursue thisline of research together, but our papers had a big influence on a series of papers
I subsequently wrote with Giovanni Sartor on formal models of presumptions andburdens of proof in legal procedure, culminating in [110]. One idea that Giovanniand I further developed was the distinction between the global and local burdens of
proof, which was one of Doug’s contributions to the two papers I wrote with him
and Chris Reed. The global burden of proof remains fixed during a persuasion
dialogue and rests on the proponent of the initial claim. By contrast the local
burden of proof can shift during a dispute. As we wrote in [106]:

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Moves in which a proposition is asserted (either as a claim or as a premiseof an argument) usually carry a burden with them to defend the assertion
or else retract it when challenged. However, in exceptional cases the burden
shifts to the other party to provide evidence that the proposition does not
hold.
This agrees with the above-sketched way of embedding reasoning with defeasible
argumentation schemes in dialogue protocols. In fact, in [105, 106] we assumed
that arguments as put forward in a dialogue are constructed with argumentation
schemes seen as defeasible inference rules. Giovanni and I found that Doug’s distinction between global and local burden of proof is related to a distinction incommon law between the burden of persuasion on the one hand, and the burdenof production and the tactical burden of proof on the other. We also further developed the idea proposed in [105, 106] to model dialogues about the burden of proof,
especially in [109].
To be honest, Giovanni and I found that Doug’s ideas on burdens of proof were
not the final answer; especially in legal contexts the notion of burden of proof isquite tricky; in [110] we distinguished no fewer than seven distinct types of proof
burdens. But Doug’s ideas definitely put us in the right direction.

8 Giovanni Sartor: Argumentation in legal interpretation

I came to know Doug about two decades ago, at one of the many ICAIL conferences
at which both of us participated. I remember that I enjoyed speaking with him, I
liked his curiosity, and his availability both to provide his insights and to listen toless experienced researchers, coming from different domains
At that time, I had already been working, in particular with Henry Prakken,
on developing formal models of legal reasoning based on logic programming, nonmonotonic logic and Dung-style argumentation. I felt committed to the project ofdeveloping formal models of legal knowledge and reasoning. I thought that suchmodels, to be built by applying and extending ideas from logic and AI, would
contribute not only to useful computer applications, but also to progress in legal thinking and legal practice. I was aware that research on argumentation andrhetorics –in particular some leading contributions, such as of Chaim Pereleman[91], Stephen Toulmin [128], and Theodor Viehweg [141]– could provide many useful insights for the development of formal models of legal reasoning. However, inlegal studies, in particular in the continental tradition, the appeal to the “informal”, “rhetorical” or “topical” tradition was often presented in a polemic opposition to any application of formal, or even scientific, methods in the legal domain.
It seemed that a legal theorist would have to choose on which side to stand, andgiven my interests and propensities, I was committed to the “formal” side, which
implied being to some extent sceptical toward “informal logic.” The encounter
with Doug changed my perspective: he was a leading scholar in informal logic, but
was interested in finding formal and even computable models that could capture,even though partially, the patterns of reasoning that he was detecting and investigating. Since his work on dialogue types with Erik Krabbe [166] he had engaged inthis interdisciplinary research, meant to merge argumentation research and formal
models. Moreover, he was interested in bringing this approach into the AI and30

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Law domain, as shown by the contributions he was developing with some of mycolleagues working in this domain.
I was very happy to be able to invite him for some months at the European
University Institute. We had a well-attended course on argumentation in law, andwe succeeded in doing some work together, which led to the following research
projects.

8.1 The rationale for argument schemes
A first project concerned the justification of argument schemes. Doug’s work had
elicited a number of diverse argumentation schemes, well beyond the classical distinction of deduction, induction, abduction and analogy. He had also shown thatreasoning patterns that were usually considered to be fallacies —arguments from
authority, from precedent, from ignorance, from correlation to causality, etc.—, asthey fail to meet the requirements of logical deduction, were accepted in a numberof contexts and domains. However, such patterns could lead to mistaken conclusions, even when deployed in suitable contexts, due to their defeasible nature.
This raised the issues of what would justify the fallible use of a defeasible reasoning pattern, in what contexts. A second issue was to explain why certain patternsof reasoning could be used legitimately in certain cultural-institutional contexts
and not in certain others. This would apply in particular to patterns used in legal
interpretation. In fact, in different legal systems different argument schemes –suchas appeals to ordinary language meaning, to legislative intention, to preparatory
work (drafting history) or to teleology– are used to different extents to support
interpretive claims. If argument schemes embody appeal to rationality, how is it
possible that their use is so parochial?
Our approach to address such issues was based on two main considerations.
First, we affirmed that argument schemes themselves could be justified througharguments. In particular, the use of argument schemes can be given a pragmatic
justification, namely, a justification based on teleological reasoning, as instantiatedby the scheme for practical reasoning, supplemented by arguments from positive
and negative consequences. Thus, the use of an argument scheme in the context
of an activity would be justified to the extent that the scheme contributes to the
cognitive or practical purposes of that activity. Second, we considered that thepragmatic utility, and consequently the justification, of a scheme may depend on
the shared acceptance of the scheme. The use of a scheme –such as appeal toordinary language or to preparatory works in legal interpretation– is justified by
the very fact that this scheme promotes engagement and persuasion, or at leastacquiescence, and this depends on the existence, in the given context, of a shareddisposition to use that scheme.

8.2 Legal interpretation as argumentation
The interaction we had in Florence led us to one further project, that was tocontinue in the following years, namely, an argument-based analysis of legal interpretation. We focused on the classifications of arguments in legal interpretationthat had been proposed by the legal theorists, such as Giovanni Tarello [125] andIn Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

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Neil MacCormick and Robert Summers [84]. It seemed to us that such jurisprudential analyses provided rich insights into legal discourse, but that additional
understanding could be gained by linking them on the one hand to argumentation
theory and on the other hand to AI and Law research. Thus, we decided to consider the extent to which interpretive discourse as classified and analysed by legal
theorists could be mapped into the argument schemes identified by argumentation
theorists such as Doug and his associates [167]. Moreover, we wanted to provide a
structured and possibly computational representations of such arguments. Fabrizio
Macagno, who had already extensively cooperated with Doug (see [167]), joined
us in this project. A number of contributions were subsequently developed, where
we merged the analysis of legal interpretation though argumentation theory andpragmatics, with the modelling of interpretative reasoning through systems for
defeasible argumentation, relying in particular on Carneades and ASPIC+ ([82],[117], [168], [83], [169]). On the one hand we showed that arguments used in legal
interpretation could indeed be classified and analysed as instances of the kinds ofargument that had been studied in argumentation research. On the other hand,
we showed that such arguments could be captured through defeasible conditionals,
together with the presuppositions/presumptions concerning their use, and possible
attacks against them (critical questions/exceptions). Thus it was possible to modelinterpretive debates through defeasible argumentation, to capture the dialecticalinteractions of competing interpretive proposals and attacks against them, as wellas the transition from the interpretation of legal provisions to their application toderive substantive conclusions.

The development of this research lead to my final project with Doug, namely,
to the idea of preparing a book on argumentation in legal interpretation. The book,co-authored by Doug, Fabrizio Macagno, and myself, entitled The pragmatic andargumentative structure of statutory interpretation, had been completed just before
Doug’ s sudden departure from us. It is hopefully going to be published within thecurrent year (2020). The book aims at providing an account of legal interpretationthat combines and integrates five different disciplines, each giving a different perspective on legal argumentation: argumentation theory, legal theory, pragmatics,
dialectics, and AI and Law. The core of the book is constituted indeed by Doug’s
approach to argumentation, as contextualised to interpretive debates. After providing an introduction to legal interpretations, argument schemes for statutory
interpretations are defined and consistently applied to multiple legal and paralegal examples. Their use is connected to the pragmatics of legal language and legal
interactions. Interpretive arguments — such as linguistic, teleological, a contrario,
and analogical arguments - are modelled as defeasible modus ponens inferences,subject to challenges and attacks. The book has two main goals, a theoretical one
and a practical one. The theoretical goal consists in linking legal argument to general argumentation, i.e., in showing how the complexity of interpretive canons andreasoning can captured by using the instruments that we already use to model
everyday conversation. The practical goal consists in furnishing tools to aid with
the interpretation of statutory texts, in particular by explicating and visualising,through argument maps, the whole network of competing arguments concerning
an interpretive issue.

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Fig. 2 Perspectives on argumentation

9 Bart Verheij: Connecting formal, computational and real-lifeargumentation

My first encounter with Doug Walton was when he gave one of the invited lectures at the International Conference on Formal and Applied Practical Reasoning(FAPR 1996) that took place in Bonn. I was then near the end of my PhD research and had been struggling with the breadth of perspectives that was helpful
and necessary for the study of argumentation in the law (Figure 2, taken from myreport of that conference16 ). One is the perspective of theories and models emphasising the formal conceptualization of argumentation, as for instance studied inphilosophical logic. A second is the perspective of minds and humans emphasising
how argumentation occurs naturally in everyday and professional domains, as for
instance studied in the cognitive sciences. And a third and final is the perspective of machines and programs emphasising a computational perspective on how
argumentation occurs.
The conference was a relief, as there a community was gathering where seemingly everyone was interested in the study of argumentation as an enterprise inbetween all these perspectives. And Doug was a central member of that community. Until then I had known him only from some of the books I had been borrowing
from the university library. I knew his Fallacies co-written with his PhD supervisor
John Woods (who survives Doug), and I knew his Informal Logic [145]. Alreadythese books (just two of already then many) suggested how prolific he was as an
author, and how broad his contributions to the study of argumentation.
In his lecture, Doug emphasised the need for the development of an ‘applied
logic’, acknowledging the pragmatic, goal-driven side of reasoning and argumentation. He also spoke of software as a critical thinking tool, a topic at the heartof the computational dialectics workshop organised by Tom Gordon and Gerhard
Brewka at that conference, which I also attended.
To me all this felt very fresh, relevant, important. Doug had at that time
already written some 20 books on these and related topics.
A second episode of Doug’s influence on me as a researcher is a workshop
organized by Chris Reed and Tim Norman in Bonskeid House, originally a Scottish mansion, but by then converted to a youth hostel. In that week, a group ofsome twenty researchers gathered with the goal to produce a book on what Chris
16

https://www.ai.rug.nl/~verheij/publications/fapr96report/, written for Ron Loui.

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and Tim referred to as ‘argumentation machines’. The book appeared four years
later [113] and contains a roadmap of research in argument in computation (byChris and Tim). Doug coauthored a chapter on argument and multi-agent systems.
The intensity of the event played a role in setting the agenda and building
the community for the computational argumentation community, to which Doug
contributed from the start: he co-wrote two papers at the first of the biennial Computational Models of Argument conference series (COMMA 2006, Liverpool) [57,58, both with Tom Gordon] and wrote a paper for the first issue of the Argument
and Computation journal [156]. Just before he died Doug had finalized a paper forthat same journal. It appeared posthumously as [159].
During the workshop in Bonskeid House, Doug discussed argumentation schemes
and their critical questions as catalogued by him in his 1996 book [146], later
adapted and expanded with Chris Reed and Fabrizio Macagno [167]. At thattime, I had just developed the DefLog formalism [136], and in that week in Scotland became aware of the fact that argumentation schemes could be given a formal
semantics in such an argumentation formalism, with critical questions corresponding to points of attack [133, 137]. The perspective became the basis of my workon argument diagramming and evaluation software [135, 138, 139], balancing reallife relevance and compliance with [42]. Now that I write this text, that work was
clearly an answer to what Doug had been calling for at the 1996 Bonn conference
mentioned earlier. Meanwhile Doug was developing his own answer to that call(e.g. [116, 58]).
Doug’s ideas on argumentation schemes also helped me with addressing the
puzzle of how to connect formal and applied logic. As a mathematician working(then) in a law school, I had been thinking hard about the relation between (onthe one hand) the formal rules of inference as they appear in mathematical logic
and (on the other hand) the reasoning patterns in law as Jaap Hage and I had beenmodeling them in Reason-Based Logic [65]. For Jaap, Reason-Based Logic was an
approximation of a natural logic, optimizing relevance for law. Our discussions led
me to write about whether a ‘logic of law’ could exist [134]. My answer was yes andno at the same time: yes, a logic of law can exist by formally explicating legally
relevant reasoning patterns (a bit like in a natural deduction system, but now a‘legal deduction system’), but also no, since such a legal logic can also be reduced
to a set of legal assumptions in a more abstract logic. When I heard Doug speak onargumentation schemes in Bonskeid, I understood that, like Reason-Based Logic,
argumentation schemes could be thought of as either being part of a contextual,applied logic, or as a set of contextual assumptions in a more abstract logic [137].
In this context, I made a proposal for a scheme ‘Modus non excipiens’, a variationof the familiar Modus ponens in the context of defeasibility, that ended up in the
Argumentation schemes book [167, p. 366]:
Modus Non Excipiens [134]As a rule, if P, then Q.
P.
It is not the case that there is an exception to the rule that if P, then Q.
Therefore, Q.

A third part of my journey with Doug and his ideas occurred when I was asked
to review some of his books for the Artificial Intelligence and Law journal, specifically The New Dialectic [148], Ad Hominem Arguments [147] and One-Sided Argu-

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Katie Atkinson et al.

ments [149]. I then discovered that for Doug, at that time, argumentation schemes
did not yet have a standardized format [132]. Concretely, in his Ad Hominem Arguments, the following three all count as argumentation schemes (here AH abbre-

viates ‘ad hominem’):
GENERIC AH (p. 249 in [147])
a is a bad person.
Therefore, a ’s argument α should not be accepted.
GUILT BY ASSOCIATION AH (p. 256-257 in [147])
a is a member of or is associated with group G, which should be morally
condemned.
Therefore, a is a bad person.
Therefore, a ’s argument α should not be accepted.
TWO WRONGS AH (p. 256-257 in [147])
Proponent: Respondent, you have committed some morally blameworthy
action (and the specific action is then cited).
Respondent: You are just as bad, for you also committed a morally blameworthy action (then cited, generally a different type of action from the one
cited by the proponent but comparable in respect of being blameworthy).
Therefore, you are a bad person, and your argument against me should not
be accepted as having any worth.
The first is an argumentation scheme in its by now more standardized format: asa kind of semi-formal rule of inference, with a schematic premise and conclusion.
The second is more like a semi-formal derivation, consisting of two steps. Now thiswould be thought of as built from two instances of an argumentation scheme. The
third is like a small boilerplate dialogue, here not even using the scheme-indicating
variables a (for the attacked arguer) and α (for the attacked argument).
One lesson that I learnt from reviewing these books is how seriously Doug took
his emphasis on applied logic: all endeavours in applied logic should be relevant
for real life argumentation. Real life relevance always comes first, and only thencareful systematization. In formal logic, things often stand the other way around.
The reviewing effort strengthened my perspective on formalizing argumentation schemes. Where first I mostly emphasised the connection between criticalquestions and argument attack, and the added value of formal evaluation [133],
I now more clearly saw how cataloguing argumentation schemes could be approached as a kind of knowledge engineering enterprise [137]. Each scheme should
follow a standard format and consist of lists of premises, conclusions, exceptions
and conditions of relevance. As a result of this four-element format, critical questions could also be divided into four kinds: questions about a premise, about aconclusion, about an exception (that I took as blocking the connection between
premises and conclusion, following Pollock’s idea of undercutting defeat [94]) andabout a condition of relevance. These ideas were clearly hanging in the air, as
several researchers (including Doug himself) were developing a similar perspective
on argumentation schemes in those days.
Floris Bex and I applied this knowledge engineering method towards argumentation schemes when we modeled theoretical approaches to evidential reasoningin terms of argumentation schemes and their critical questions: first, we modeled

In Memoriam Douglas N. Walton: The influence of Doug Walton on AI and Law

35

the anchored narratives theory [144], that provides a normative perspective on
evidential reasoning in terms of good quality, well-supported scenarios explaining
the evidence [140]; then the hybrid theory of evidential reasoning [28], that shows
how evidential reasoning with arguments and with scenarios go together [31]. Doughimself also continued to have an interest in evidential reasoning and argumentation (e.g. [158]).
When I try to summarize Doug’s influence on me, my thinking and my life,
Doug showed that:
1. an applied version of logic can be pursued in terms of argumentation schemes,
and gives an all-encompassing perspective on argumentation relevant for all
aspects of life;
2. the critical questions that come with argumentation schemes directly suggest
possible points of attack of arguments, thereby providing the means to both
evaluate arguments and produce a debate;
3. real life examples and case studies are a necessary and concrete approach tolowering the risk of sterile theorizing without sufficient real life relevance;
4. a mix of formal and non-formal methods can provide a semi-formal middle
ground counterbalancing mathematical strictness, a bit like in AI’s knowledge
representation;
5. an inclusive, welcoming and curious attitude towards researchers and theirresearch is the best way to support the development of ideas and make progress.
The last time I saw Doug in person (as always accompanied by his wife Karen)
was in my university’s town when he was attending the most recent edition of theEuropean Conference on Argumentation (ECA 2019, Groningen). It has always
been a pleasure and an inspiration to follow Doug and his work, and I keep goodmemories of our encounters, in writing and at academic events.

10 Concluding Remarks

In this paper we have, as a group of friends and colleagues, described how Doug’s
work influenced us and the field of AI and Law. Although we have built on thesame work, we have often taken it in different directions, which is a testimony
to the richness of the ideas. What is remarkable is that Doug has worked with
us in taking it in these different directions, which reflects his lack of dogmatism,his generosity as a collaborator, and his intellectual curiosity. The AI and Law
community was fortunate that Doug became an active participant in its work, andwe, like many others, will miss both his ideas, and him as a person.

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