Analyzing Stories Using Schemes
F.J. Bex
1
Introduction
Since the early nineteen eighties stories, or sequences of states and events, play an importantpart in theories on how judges, jurors or police investigators reason with the evidence incriminal cases. Authors such as Bennett and Feldman (1981) and Pennington and Hastie(1986, 1993) argue that decision making in criminal cases is done by constructing stories
about „what happened‟ using the evidence in the case and then comparing these stories, thus
trying to find the best story, that is, the story which is accepted as most probable. A goodstory should not only be supported by evidential data (e.g. testimonies, forensic data) but itshould also be well-structured and plausible; a well-structured story is built in such a waythat is easily understandable and a plausible story correctly describes a general pattern ofstates and events one expects to come across in the world. Crombag et al. (1993, 1994) also
argued that a well-structured and plausible story is important in judicial decision making.
However, they also found that in many cases a good or plausible story which is insufficiently
supported by evidence wins over a bad or implausible story which is supported by evidence.
To overcome this problem, Crombag et al. proposed their anchored narratives theory (ANT),
according to which a story should be sufficiently anchored in reality using safe
generalizations1. This anchoring of stories in reality also plays an important part in theinvestigative phase of a case (de Poot et al. 2004), where stories serve as guidelines in the
search for new evidence. Twining (1999) and Anderson, Schum and Twining (2005)
maintain that stories are psychologically necessary in the determination of the facts of a case,in that a story is used to organize and present the evidence in such a way that it is easily
understandable. Like Crombag et al., they point to the dangers of stories and develop a
simple protocol for analysing the plausibility and evidential support of stories.
In sum, the main idea in the research of the last decades seems to be that while stories
play an important part in evidential reasoning, one should be wary of the dangers involved inreasoning with stories: in Twining‟s (1999) words, stories are „necessary but dangerous‟. In
order to overcome the danger of a good story pushing out a true story, stories have to be
critically analysed – both the plausibility (whether or not the story conforms to safe generalknowledge about the world around us) and the evidential support (whether or not the story
conforms to the specific evidential data in the case at hand) are important to consider.
Pennington and Hastie as well as Anderson et al. agree that these two aspects of stories,
plausibility and evidential support, can be tested and analysed separately. Crombag et al.
make a less clear distinction between these two aspects but they mention two types ofgeneralizations in which stories can be anchored. Of the first type are generalizations which
point to the plausibility of the story irrespective of the evidential data in the case; thesegeneralizations can be causal generalizations, which are about the chain of events in the main
1

Generalizations are general „rules‟ about how we think the world around us works (Anderson et al. 2005).
They can be based on empirical research but they can also be drawn from everyday experience. Not all of thesegeneralizations are safe as they can be based on prejudices and dubious ideas about the world. Examples ofgeneralizations are „coroners can usually determine for how long someone has been dead‟, „witnesses underoath usually speak the truth‟ and „people from Suriname are more prone to becoming involved in crime thanDutch people‟.

story itself, or other generalizations which cover the point of the story or a specific event in
the story. Of the second type are evidential generalizations, which link a story to the available
evidence. Bex, Prakken and Verheij (2006, 2007) have clarified this distinction between the
two types of generalizations and argued that a story‟s plausibility can be analysed by looking
at the causal generalizations in the story itself while the evidential support can be analysed bylooking at the evidential generalizations linking the sources of evidence to the story.
However, the causal links between the events in a story are not always explicit so it is notalways possible to immediately analyze the causal generalizations in the story. In its mostbasic form a story is a sequence of events which are ordered in time and thus the only
relations between the events are temporal. In such a case, where the causal relations between
the events are not explicitly mentioned, these generalizations will have to be made explicit
and/or other ways will have to be found to analyze the story‟s plausibility.
Pennington and Hastie argue that a story‟s plausibility also depends on the extent that itconforms to what they call an episode scheme. This idea of an episode scheme is based on theidea of a script or explanation pattern. Schank and Abelson (1977; Schank 1986) argue thatknowledge about the world can be expressed as a script or explanation pattern, which
specifies the elements a typical story has. A scheme can be abstract or more specific; forexample, a scheme for „intentional actions‟ specifies a pattern of event types that a typicalstory about some intentional action contains and a „restaurant‟ scheme describes a pattern of
events that a typical story about a visit to a restaurant contains (e.g. ordering, eating, paying).
The relations between the events in a story scheme can be causal but a very basic story
scheme does not contain causal information so it can be used to asses stories which do notcontain causal information. Furthermore, a story scheme can also help to make the implicit
causal relations in a story clearer; if a simple, temporally ordered story fits the sequence of astory scheme then the causal relations between the events in the story are also based on thecausal generalizations in the scheme.
The aim of this article is to investigate the notion of story schemes, a pattern of eventsor event types similar to the episode scheme or explanation patterns. Story schemes, theirstructure and features, will be modelled in a semi-formal way and it will be examined how
these schemes can be useful in the analysis of stories. The similarities and differences
between the notion of story schemes and my previous work (Bex et al. 2006; 2007) will be
discussed, and I will also add two simple but not trivial operations to the framework from
(Bex et al. 2007).
While this article does not concentrate on the specific roles story schemes and ananalysis using these schemes can play in reasoning about evidence, some ideas about thepossible roles of story schemes in different contexts will also be briefly discussed.
Because of the important role the plausibility of stories plays in reasoning withevidence, this article is devoted to analyzing and assessing this plausibility. The plausibilityof a story can be determined irrespective of the evidence in a case; as was argued before,plausibility and evidential support are different aspects of a story. However, this does notmean that I consider the evidential support of a story and the analysis of this evidential
support unimportant; when reasoning with evidence in a criminal case, the evidential support
of a story is the most important part, as we do not want good stories that have little or noevidential support to win over bad stories that have more evidential support. In our previous
work (Bex et al. 2006, 2007), which will be briefly summarized in section 2, we alreadyextensively discussed how evidence can support a story through evidential generalizations,
how these generalizations can be tested and how the evidence can influence the choice
between different stories.
The rest of this article is organized as follows: section 2 discusses the existing researchon the use of stories in legal reasoning, including the previous more formal research on
stories and evidence (Bex et al. 2006, 2007) in section 2; at the end of section 2 I will give
examples of two operations on causal generalizations that can aid in the analysis of suchgeneralizations. The first part of section 3 briefly summarizes existing work on story
grammars, scripts and explanation patterns; the second part of section 3 discusses thefeatures of story schemes, which are derived from the earlier work on explanation patterns. In
section 4 an example will be given of how the analysis of stories using schemes can takeplace and it will be discussed how the plausibility of a story scheme can be tested. Section 5
discusses some of the possible roles story schemes and an analysis using story schemes could
play in different kinds of evidential reasoning and section 6 concludes with a discussion andsome ideas for future research.
2
Stories: necessary but dangerous
In this section existing research on the use of stories in legal decision making and crime
investigation will be summarized, showing the different ways in which stories can be used inreasoning with evidence. In this summary, the focus will be on how in the existing research
the plausibility of stories is defined and assessed. This section is divided into two subsections:first, the research from legal psychology and legal theory on stories and story plausibility will
be discussed and in section 2.2 my previous work on developing a logical model of thisresearch will be summarized.
2.1

Stories in legal evidential reasoning

By analysing the way all kinds of different decision makers in criminal trials (judges, jurors,
attorneys) reason and make decisions about the case at hand, Bennett and Feldman (1981)
found that judicial decision making depends on the construction of different stories aroundthe available evidence. According to Bennett and Feldman, a story is organized around acentral action or central event, which is essential to the plot of the story, and the rest of thestory should act as the context to this central action. Background knowledge about the world
allows us to establish connections between the central action and the other elements of thestory. A plausible story is a story in which all the necessary connections between theelements of the story are present and these connections are based on unambiguous world
knowledge; thus a plausible story is, in Bennett and Feldman‟s words, „structurally
unambiguous‟.
An interesting observation by Bennett and Feldman is that the most plausible story is
the story that is often taken to be true. Bennett and Feldman show this with an experiment:
they asked 85 students to assess the truth of a number of stories that were told by the otherstudents. Some of these stories were really true (that is, the events recounted had really
happened) and other stories were made-up. Some of the stories (both true stories andmade-up stories) were complete and unambiguous but other stories were incomplete andambiguous. It turned out that there is a significant relation between the structural ambiguity

of a story and its credibility. That is, the more plausible a story, the higher the probability thatthe story is judged true, irrespective of the actual truth of the story.
Pennington and Hastie (1986, 1993) further developed the idea of a story in a criminal
context. They proposed a model of judicial decision making based on stories and tested it onhuman subjects. The model proposed consists of three stages which represent the stages alegal decision-maker goes through when evaluating evidence. First, the decision makers
construct stories using the available evidence, knowledge about story schemes andknowledge about similar events. These stories are then evaluated using certainty principles
and the best story is then matched to a verdict.
In Pennington and Hastie‟s work, a story has a standard structure: the basic form of astory is a simple sequence of events and a scheme can be imposed upon such a sequence. This
scheme divides the different events in the story into different categories, where each category
stands for a different role that an event or a sequence of events can fulfil. Such a scheme iscalled an episode, and is a basic model about intentional actions (figure 1). This scheme is a
simplified version of the scheme Pennington and Hastie proposed in their earlier work
(Pennington and Hastie 1986). The links in this model are causal links and thus the model
imposes a simple causal structure upon the basic story in accordance with the meaning of andrelations between the separate states and events.
Initiating states

Psychologicalstates andevents / goals

Actions

Consequences

Physical states

Figure 1: Pennington and Hastie's episode scheme

After a number of stories have been constructed around the evidence, the decision makershould decide which story to accept. Pennington and Hastie proposed two certainty
principles for determining „what the best story is‟: coverage and coherence. The story‟scoverage stands for the extent to which the story conforms to the evidence presented at trial.
The idea here is that the more evidence covered by the story, the more confidence a
decision-maker will have in that particular story. A story‟s coherence, which is similar to thenotion of plausibility mentioned before, depends on three factors: consistency, plausibility2and completeness. A story should be consistent in that it does not contain internal
contradictions between different parts of the story. A story is plausible if it conforms to thedecision maker‟s general knowledge of the world3 and a story is complete when all of theelements from figure 1 are part of the story.
The final stage in Pennington and Hastie‟s model involves matching the chosen story
to a verdict category. For example, if there is a story of one man killing another, the decision
maker can choose between the verdict categories of first-degree murder, second-degree
murder, manslaughter and self-defence (not guilty). In the table below an example of one of
2 Pennington and Hastie see plausibility as a „sub-criterion‟ of coherence; my definition of plausibility in thisarticle is similar to Pennington and Hastie‟s coherence.
3
In Pennington and Hastie‟s definition, a story‟s plausibility is relative to the person assessing the story. An
objective definition of a story‟s plausibility is more problematic, see the end of this section.

their verdict categories is given.
Verdict
Category
First-degree
murderIdentity

Mental State

Circumstances

Actions

Right person- Intent to kill
- Insufficient- Unlawful- Purposeprovocation
killing
formed- Interval- Killing- Resolution to between
pursuancekillresolution and resolution
killing

inofNotice how the different attributes of the verdict category correspond to the elements of theepisode scheme from figure 1: the Mental State corresponds to the psychological states andgoals, the Circumstances correspond to the initial states and physical states and the Actions
correspond to the actions in the episode scheme.
Pennington and Hastie tested their model on 26 jurors whom they asked to look at are-enactment of a murder trial. From the tests it followed that almost all subjects organized
the evidence as a story of „what happened‟ before deciding on a verdict and that most stories
followed the episode structure as shown in figure 1. An interesting observation was that the
subjects filled in certain elements of the episode scheme to make complete stories. On
average, a story constructed by a test subject consisted for about 55% of elements which weredirectly inferred from evidence and about 45% of the elements of a story – mainly
psychological states and goals – were not inferred from evidence but added by the subjects tomake a more complete story.
From Bennett and Feldman‟s as well as Pennington and Hastie‟s tests it follows thatstories play an important part in reasoning with evidence, in that they help people organize
the evidence and make sense of a case. Constructing stories also helps people to fill gaps in acase, as Pennington and Hastie‟s experiment shows. For example, it is often hard to directly
infer from evidence that the suspect had bad intentions. In most cases, these intentions must
be inferred from the actions that the suspect performed; in other words, these intentions canbe inferred from the story. However, this research also shows that there are dangers inherent
to stories, as Bennett and Feldman found that a good story can push out a true story.
Bennett and Feldman argue that a story‟s plausibility can be tested by looking for
ambiguous connections in the story. This is, in my opinion, too vague, especially because thenotion „ambiguous connections‟, or unsafe background knowledge, is not defined. Rather, in
Bennett and Feldman‟s theory classifying a connection as such is done intuitively, as if
decision makers are naturally adept at analysing general knowledge about the world aroundus. Furthermore, Bennett and Feldman‟s work does not discuss the evidential support ofstories.
Pennington and Hastie give clearer criteria for assessing stories: the criteria ofcompleteness and consistency are clearly defined and ensure that the story is structurallysound and conforms to a general scheme of human intentional action we expect to find in theworld. It is still unclear, however, how a story should conform to general knowledge of theworld and thus when a story can be considered plausible.

Crombag, van Koppen and Wagenaar (1993, 1994) further investigated how we canmake sure that a story is plausible in that it corresponds to general knowledge of the world.
They argued that a story should fit and conform to the general episode scheme proposed by
Pennington and Hastie. However, a story also has to be anchored using general knowledge of
the world around us, and accepting a story is done by accepting a number of generalizations
which act as anchors to the story. This is best explained by an example. Consider the caseabout Haaknat, adapted from Crombag et al. (1994, 138):
John Haaknat is a drug addict who is desperately in need of money. He knows that the owner of thelocal supermarket brings his earnings to the bank every Friday, so he decides to rob the owner when
he exits the supermarket. Together with a friend who owns a car, they wait outside the supermarket.
When the owner exits the supermarket with the money to go to the bank, Haaknat get out of the car
and points a gun at the owner, shouting „give me the money‟. The owner fears for his life so he hands
Haaknat the money. Haaknat then gets into the car and drives off in the direction of a nearby park.
The police start searching for Haaknat in the park and they find him hiding in a moat.

If we decide to believe the story about Haaknat, we also believe the generalization„eye-witnesses can reliably identify people‟, as Haaknat was identified by the owner andother witnesses. Crombag et al. consider only one type of generalization, namely those thatlink the evidence, in this case a testimony, to the story.
Crombag et al. argue that the generalizations which act as anchors have to be safe forthe ultimate decision to be rationally better motivated and not based on dubious
generalizations. Say, for example, that there is evidence that at the time of the robbery it was
dark outside. The generalization „eye-witnesses can reliably identify people‟ can be mademore specific: „eye-witnesses can reliably identify people they saw in the dark‟. Clearly, thisgeneralization cannot be regarded as safe knowledge about the world.
Crombag et al. discuss in detail how generalizations can be analysed in this way anddecision makers are urged to make the world knowledge they use to come to their decision
explicit, so that the ultimate decision is better motivated and not based on dubious
generalizations. However, exactly when a generalization is safe is not made clear and thedetails of what part the generalizations play in a story are left untreated.
Twining (1999) and Anderson, Schum and Twining (2005) argue that a story is „widely
regarded as appealing to intuition or emotion and as a vehicle for irrational means of
persuasion‟. However, they recognize that stories are psychologically necessary in that they
help people make sense of the world and of the events that happened in a particular case.
Anderson et al. give a simple protocol for analysing the plausibility, coherence andevidential support of stories. This protocol consists of a list of questions; some questions
point to the evidential support for the story, for example „to what extent does the evidence
support the story?‟ and „is there evidence that conflicts with the story?‟ Other questions aremeant for analysing the plausibility of the story, for example „is the story supported byplausible background generalizations?‟ or „does the story fit a familiar story such as
Cinderella and what is the relevance of this?‟. So in Anderson et al.‟s work, story plausibility
is tested by looking at the background generalizations; here, a story‟s plausibility is not tested
by looking at whether it fits a plausible episode scheme, but it is tested by analyzing thegeneralizations which act reasons to accept the story. For example, If we decide to believe

the story about Haaknat, we also believe the generalizations „people fear for their lives when
they have a gun pointed at them‟ and „people value their life higher than money‟ – this
explains the owner‟s behaviour. These kinds of generalizations can also be made more
specific. Say, for example, that there is evidence that Haaknat used a pink toy gun to threaten
the owner of the supermarket. The generalization „people fear for their lives when they havea gun pointed at them‟ can be made more specific: „people fear for their lives when they havea pink toy gun pointed at them‟. Again, the more specific generalization cannot be regarded
as safe knowledge about the world.
Furthermore, Anderson et al. argue that well-known stories, such as Cinderella, also
affect our judgement of a story‟s plausibility. However, like the other authors mentioned here
they do not give a thorough analytic account of how exactly these backgroundgeneralizations and general stories serve as a tool in the analysis of stories.
The research discussed in this section seems to agree on the fact that the plausibility ofa story can be analysed by looking at to what extent the story conforms to plausible
background knowledge of the world. However, the notion of „plausible world knowledge‟ issomewhat problematic. According to Cohen (1977), the plausibility of our world knowledge
depends on our „stock of knowledge‟, which is accepted through a cognitive consensus
within a given group of people (for example, a society): if a generalization or episode scheme
conforms to this stock of knowledge, it can be judged as plausible. Anderson et al. (2005)
argued that this cognitive consensus about the stock of knowledge is a problematic notion: inany given group of people there will always be disagreements about which knowledge toaccept as plausible and the idea of a general consensus is almost impossible in a dynamic,
multicultural and multi-class society. However, it is possible and necessary to accept that
there is a certain consensus about knowledge of the world; otherwise we would not be able todraw any conclusions. To meet any dangers posed by differences or arguments regarding
generalizations or episode schemes, these generalizations should be as explicit and elaborate
as possible. So while the ultimate conclusion about the plausibility of a generalization or
episode scheme depends on the person(s) making this decision and their stock of knowledge,
this conclusion about the plausibility is stronger to the extent that it is based on explicit anddetailed generalizations.
2.2

Formal argumentative story-based analysis of evidence

In (Bex et al. 2006, 2007), we aimed to construct a theory that combines causal stories4 andevidential arguments. The main reason for developing this combined theory was to givesources of evidence, or evidential data, a more prominent place in a theory for reasoning
about evidence with stories. This combined theory, which will be briefly summarized below,
also allows for the critical analysis of the causal links within in the story.
The basic idea of the combined approach is as follows. A logical model of abductive
inference to the best explanation (IBE)5 takes as input a causal theory (a set of causal rules or
4

It should be noted that we use a naïve interpretation of causality; sometimes a causal link does not represent amuch stronger relation than temporal precedence.
5
See (Lucas 1997) for an overview of abductive reasoning and (Thagard 2004) for a slightly different take on
IBE.

generalizations) and a set of observations that has to be explained, the explananda, andproduces as output a set of hypotheses that explain the explananda in terms of the causal
theory. The combination of hypotheses and causal theory can be seen as a story about whatmight have happened. These hypothetical stories or explanations can then be comparedaccording to the plausibility of their causal generalizations and the extent to which they
conform to the sources of evidence in a case. These sources of evidence (e.g. witness
testimonies, forensics reports) are connected to the stories by defeasible arguments, that is,arguments which can be attacked and defeated. For example, an argument with the premise„the owner testified it was Haaknat who robbed him‟ and the generalization „eye-witnesses
can reliably identify people‟ has as its conclusion „Haaknat who robbed the owner of thesupermarket‟. This conclusion is an event in the story on page 6. Note that evidential
generalizations can also be attacked by arguments. For example, if we have evidence that therobber wore a mask during the robbery, the generalization that eyewitnesses can reliably
identify people can be attacked.
Defeasible arguments are also used to attack explanations: the causal rules of thetheory are not just given but their applicability can become the subject of an argumentation
process. For example, the causal generalization „people fear for their lives when they have a
gun pointed at them‟ can be attacked by arguing that in this case the generalization is notapplicable because the gun was a pink toy gun.
Figure 2 shows an abstract graphical notation of stories as causal networks andarguments. In the figure, events that are not supported by evidence are in a dotted box andevents that are supported by evidence in a box with a solid line. This is a semi-formal way ofrepresenting them, but a formal translation into well-known formalisms is straightforward(see Bex et al. 2007).
If there is more than one explanation for the explananda, they must be comparedaccording to their plausibility and their conformity to the evidence in a case. The plausibilityof an explanation is judged by looking at the plausibility of the causal generalizations in thecausal theory. If a causal generalization is deemed implausible, it can be attacked with anargument: the more causal generalizations are attacked by arguments the less plausible a
story is.

causalgeneralization

causalgeneralization

event
evidential
generalization

event

event

event

event

explanandum
evidential
generalization
source of evidencecausalgeneralization

A story explaining an explanandumevent

An evidential argument with an
event as its conclusion

event

An argument attacking a
causal link in a story

An argument attacking anevidential link in anotherargument

Combining a story and evidential arguments

Figure 2: stories, arguments and generalisations

An explanation‟s conformity to the evidence in a case, or its evidential support, can bemeasured by looking at how many events in the explanation are supported by an argumentthat is not attacked: the more events in the story follow from evidential arguments, the betterthe story is.
In the model of (Bex et al. 2007), the causal generalizations in a story cannot bechanged; they can only be attacked. Bex and Prakken (2004) defined two ways of refining
generalizations in an argumentation context; these same operations can be defined for causal
generalizations. Firstly, a causal generalization can be made more specific by explicitly
adding the „hidden conditions‟. For example, say that we have a generalization „if someone
wants to rob another person, this may cause him to threaten that person with a gun‟. One ofthe preconditions for this causal inference to be made is that the person who threatens with a
gun actually has a gun, viz.:
X wants torob Y

X threatens Y
with a gun

X wants torob Y

X threatens Y
with a gun

X has a gun

Figure 3: adding hidden conditions to a generalization

Thus the generalization is changed into „if someone wants to rob another person and he has agun, this may cause him to threaten that person with the gun‟.
Secondly, a causal generalization can be changed into a more specific generalizationby „unpacking‟ it, changing one causal link into a causal chain:

X hands over
G to YX threatens Y
with a gun

X threatens Y
with a gun

Y is afraid

Y hands over
G to X

Figure 4: unpacking a causal generalization

Here the causal generalization „If someone (X) threatens another person (Y) with a gun, thisperson will hand over his belongings (G)‟ is changed into two generalizations, namely „Ifsomeone threatens another person with a gun, this person will be afraid‟ and „If a person isafraid, he will hand over his belongings‟.
To summarize, evidential arguments require one to make explicit the evidential
generalizations used and exceptions to these generalizations can be given, thus allowing for a
critical analysis of the connections between the evidence and the story. Explicitly modellingthe causal generalizations in the causal theory allows for a thorough examination of thesegeneralizations: they can either be changed by exposing hidden conditions or by unpacking,and they can be can be questioned by attacking the generalizations with arguments. However,as was mentioned in section 1, a story‟s causal generalizations are not always explicit, soways will have to be found to make these generalizations explicit or other ways will have to
be found to analyse a story‟s plausibility. Furthermore, the current formal theory also does
not allow us to measure the extent to which a story conforms to the intentional episode in theway that Pennington and Hastie proposed. To allow these other ways of analyzing stories, theformal theory must be expanded by introducing story schemes. In the next section, this will
be discussed and in section 4 it will be shown how stories based on schemes can be analyzed
in more ways than stories based on causal theories.
3
Story schemes
In the seventies of the last century, the fields of cognitive science and artificial intelligencealso took an active interest in stories. This research first mainly focused on developing
formal grammars for describing the structure of a typical story. Pennington and Hastie‟sepisode schemes borrow heavily from the story grammars proposed by Mandler and Johnson(1977) and Rumelhart (1975). These story grammars also divide stories into episodes, which
consist of a beginning, development (containing mental responses, goals and actions) andconsequences. The episodes consist of either other episodes or individual events. The events
linked by causal as well as a temporal links, as both sentences of the form „event A THEN
event B‟ as well as „event A CAUSE event B‟ can be constructed in the grammars.
In later research the attention shifted towards story understanding by using a set of„general action sequences‟ or scripts (Schank and Abelson 1977; Schank 1986). While
Schank and Abelson (1977) also use a basic episode scheme, they also argue that story
understanding is also done by using more specific and detailed information about standard
patterns of actions when reading and understanding stories. These standard patterns orsequences are modelled as scripts; the much quoted „restaurant-script‟, for example, contains
information about the standard sequence of events that take place when somebody goes todine in a restaurant. Scripts help us to understand stories by filling in missing information. As

an example, take the following (very short) story:
Nicola went to a restaurant. He asked the waitress for a plate of spaghetti. He paid the check and left.

This story is understandable because it references to the restaurant script. Not all of thedetails (Nicola taking off his coat, Nicola reading the menu etc.) have to be mentioned
because they are assumed to happen when somebody goes to eat in a restaurant.
In his later work, Schank (1986) talks about explanation patterns (XPs), which contain
information to understand the different events in the story and why they happen as they do.
These XP‟s are similar to scripts in that they contain a standard sequence of events. An
important difference is that Schank explicitly mentions that XPs are used to explain an event:they connect the event with world knowledge, namely an explanation that has been used in
the past to explain the event. As an example, take the XP for „robbery‟ (in the broadest senseof the word):
Robbery explanation pattern:
1. Event that the pattern explains: person Y loses (physical) ownership of goods G
2. Events which are necessary for the pattern to be a valid explanation: Y loses
ownership of G, person X robs person Y
3. Events under which the pattern is likely to be relevant: X wants G
4. Pattern of actions: Y owns G – X wants G – X wants to rob Y of G – X has anopportunity to rob Y – X robs Y – Y loses G
5. Other relevant information: the time of the robbery, the place of the robbery, thetype of force employed, the nature of the goods G
6. More specific kinds of robbery: armed robbery, mugging, carjacking
This XP is slightly different from Schank‟s version of an XP but the main idea is the same.
Element 1 is the event that the pattern explains. Note that a pattern can explain more than one
event; for example, the robbery XP can also be used to explain the fact that „X has G‟.
Elements 2, 3, 5 and 6 speak for themselves. Element 4 is perhaps the most important part of
the XP; as Schank puts it, the pattern of actions, or scenario, is “essentially a little story thatis a carefully constructed causal chain of states and events [that explains the event to be
explained]”. While the examples of patterns of actions Schank gives all seem to be causallyor at least temporally ordered, the exact causal relations between the events is often left
implicit.
Both the episode schemes proposed by Pennington and Hastie and the explanation
patterns proposed by Schank can be seen as instances of something which I will call story
schemes. These schemes divide the different events in the story into different categories
ranging from abstract (Pennington and Hastie‟s episode scheme) to more specific schemes(explanation pattern-schemes). In this article, story schemes will be modelled as an ordered
list of events or types of events together with the possible relations between these events6.
6

In this article, story schemes are represented through figures, where elements of a scheme are represented byboxes and (causal) relations are represented by arrows. This is a semi-formal way of representing them, but aformal translation along the lines of (Bex et al. 2007) is straightforward.

These relations will usually be causal relations, but they can also be temporal relations. Like
the causal theories from section 2.2, which can abductively explain events, story schemes canalso be used to explain certain events; an explanation pattern includes an explicit element„event to be explained‟. In this way, story schemes can explain events without the use explicit
causal information.
Story schemes can be abstract or specific; for example, the robbery scheme contains
general instances of quite specific events (e.g. „X robs Y‟), while Pennington and Hastie‟sscheme for intentional action (figure 1) contains more general event types (e.g. ‟actions‟).
The more specific schemes can sometimes be seen as instances of the more abstract schemes;for example, a robbery is an instance of an intentional action. In this way, different story
schemes can be said to match each other: a story scheme S1 matches a story scheme S2 to theextent that the elements in S1 correspond to the elements in S2. The correspondence relations
between the elements of the intentional action and the robbery scheme are shown in figure 5:
Initiating states

Y owns G

X wants G

Goals

Physical states

Actions

Consequences

X wants torob Y

X has anopportunity
to rob Y

X robs Y

Y loses G

Figure 5: the correspondence relations between the intentional action and the robbery scheme

These correspondence relations between the elements of the different schemes can be
expressed as generalizations. For example, „X robs Y expresses an action‟. These
generalizations have to be plausible: when such a generalization is implausible, the two
schemes do not match. For example, the correspondence generalization „Y owns G expresses
a goal‟ is not plausible so there is no correspondence relation between these elements. Notethat correspondence relations and generalizations can be attacked by arguments in the same
way that evidential and causal generalizations can be attacked (see section 2.2).
Sometimes two matching schemes only differ on one or two elements. For example,
the element „X robs Y‟ in the robbery scheme can also be modelled as two separate elements,„X threatens to use force against Y‟ and „Y hands over G to X‟, thus making the concept of„robbery‟ more specific.
Another aspect of story schemes that has to do with the correspondence between
different elements of schemes was already noted by Pennington and Hastie: the so-calledhierarchy of episodes. Story schemes are hierarchical, in that each component of an episodemay correspond to an episode itself. In figure 6, this recursiveness of the intentional action
scheme can be seen. For simplicity‟s sake, some elements of the episode have been left out.
Initiating states and events
Initiating states

Actions

Consequences

Actions

Consequences

Figure 6: recursive story schemes

Here, the Initiating states and events correspond to a separate sub-episode.

If two story schemes match, there is usually also a correspondence between the causal
relations in the different schemes. For example, the causal relations of the intentional action
scheme (figure 1) can be inserted in the robbery scheme because the elements of theintentional action and the robbery scheme correspond:
X wants G
Y owns G

X wants torob Y

X loses G

X robs Y

X has anopportunity to rob Y

Figure 7: the robbery scheme with a more detailed causal structure

In this way, more abstract schemes which causal relations are generally agreed upon can beused as a tool for making the causal generalizations in a specific story scheme more explicit.
Note that figure 7 also contains an example of a hierarchical episode: „A wants G‟ and „Bowns G‟ are a separate sub-episode of the robbery scheme. In the figure, the causal relationsin this sub-episode have been left implicit.
In this section the basic structure and features of story schemes have been discussed
as well as ways to specify story schemes. Story schemes are similar to causal theories as
discussed in section 2.2 in that they can be used to explain events. However, explaining
events with story schemes is perhaps somewhat simpler: where in a causal theory all thecausal generalizations have to be made explicit story schemes allow us to explain events byproviding only the general pattern of events. This carries a risk, as implicit causal
generalizations can be of dubious quality. Using more abstract schemes as a tool for making
the causal generalizations in a specific story scheme more explicit allows us to analyze andassess the more specific causal generalizations and thus part of this risk is overcome. In thenext section it will be shown how the plausibility of simple story schemes can be analyzed
and assessed.
4
Analysing stories
A story is essentially a particular version of a story scheme, where the variables have been
replaced by constants. Recall that in section 3 a story scheme for robbery was given; theHaaknat story is a particular instance of this scheme, viz.:
Haaknat
wants
money

The owner of thesupermarket has
money

Haaknatwants to rob
the owner

Haaknat has an
oppurtunity to
rob the owner

Haaknatrobs theowner

The owner lost
his money

Figure 8: the Haaknat story

Here X in the scheme has been instantiated with „Haaknat‟, Y has been instantiated with „theowner‟ and G has been instantiated with „money‟. In this way, each story has an associatedstory scheme of which it is an instance. Here, the parallel between a story scheme and acausal theory as defined in section 2.2 can be seen. A causal theory is a collection of causal
generalizations which, when the variables are instantiated, forms a story. A story scheme issimilar to a causal theory, but in a story scheme the different events are not always linked andif there is a relation between events this relation is not necessarily causal but sometimes
temporal. In this way, a story scheme is a less specified version of a causal theory that also
allows for stories that do not contain explicit causal information.
In section 2.2 it was argued that the plausibility of a story can be analyzed by looking at
the plausibility of the underlying causal theory, so in the same way it can be argued thatanalyzing the plausibility of a story that is based on a scheme can be done by looking at theplausibility of the underlying story scheme. Schank (1986) also argues that a plausible
explanation pattern provides the natural context for the event it explains in the
belief-goal-plan-action chain. If this condition for the plausibility of story schemes is added
to the earlier condition that the individual causal generalizations in the scheme or theory
should be plausible and sufficiently detailed, there are two criteria for determining whether
or not a story scheme (and thus a story based on the scheme) is plausible. Firstly, a story
scheme should match the intentional action scheme; this ensures that the scheme adheres to
the general goal-action chain as proposed by Schank and it also ensures that the scheme
conforms to Pennington and Hastie‟s intentional episode scheme. Secondly, the causal
structure and the causal generalizations of the scheme should be plausible and sufficiently
detailed. So a story is plausible and sufficiently detailed if its associated story scheme
matches the intentional action scheme and if the causal generalizations in the associated story
scheme are plausible and sufficiently detailed. In the rest of this section, a story is said to fit astory scheme S to the extent that its associated story scheme matches S and vice versa. For
example, Haaknat‟s story as detailed above completely fits the intentional action scheme
because the story scheme associated with Haaknat‟s story, the robbery scheme, completely
corresponds to the intentional action scheme and vice versa (see figure 5).
The causal structure of the Haaknat story as shown above is not very detailed. However,it can be matched to the robbery scheme from section 3; often, a story does not contain
explicit causal information but a story scheme does and matching the story to the scheme cangive the story an explicit causal structure. As long as the story itself contains no explicit
causal relations that contradict the causal relations in the story scheme, the causal relations
from the scheme can be used in the story. In this way, the Haaknat story can be updated withthe more detailed causal structure from figure 7, providing us with the following story:
Haaknat
wants
money

The owner of thesupermarket has
money

Haaknatwants to rob
the owner

Haaknatrobs theowner

The owner lost
his money

Haaknat waits
outside thesupermarket

Figure 9: The Haaknat story with a clear causal structure

Note that in figure 9, „Haaknat has the opportunity to rob the owner‟ has been replaced with„Haaknat waits outside the supermarket‟. This story still fits the robbery scheme because
waiting outside the supermarket can be seen as having an opportunity to rob the owner of thatsupermarket.
To give an example of a less plausible story, consider Haaknat‟s version of the events that

explains why he was found in the moat. Haaknat testified that an hour before he was found,he had an appointment with Bennie, who owed him some money. Bennie did not want to pay
back the money and Haaknat and Bennie got into an argument, during which Bennie drew aknife. Haaknat felt threatened by Bennie and he ran away. After a while, Haaknat sees thepolice officers looking for someone in the park, and he jumps into the moat to hide. Sometime later, the police find Haaknat in the moat. The story scheme associated with this story
can be written down as follows:
Argument
between X and Y

Y drawsknife

X feels
threatened by Y

X runsaway

X runs into
policeX hides inmoat

Police find X
in moatFigure 10: the ‘hide after threatened’ story scheme

The story can be represented in the same way by instantiating X with Haaknat and Y with
Bennie. This story can be modelled as two episodes, where the first episode is „Argument
between X and Y – Y draws knife – X feels threatened by Y – X runs away‟ and the second
episode is „X runs into police – X hides in moat – police find X in moat‟. However, when we
model the story in this way, it does not fit the intentional action scheme, because thepsychological states/goals element does not correspond to events in the story:

Argument
betweenHaaknat andBennieHaaknat feels
threathened by
BennieBennie draws
a knifeHaaknatruns away

Initiating events

Psychologicalstates / Goals

Haaknatruns into
policeHaaknathides in amoat

Police findHaaknat in moat

Physical events

Actions

Consequences

Figure 11: Haaknat's version of the story matched to the intentional action scheme

Alternatively, one could argue that „Haaknat feels threatened by Bennie‟ is the psychologicalstate in the above story scheme; then the story is modelled as a single episode:Psychological states
Argument
betweenHaaknat andBennieBennie draws
a knife

Initiating events

Haaknat feels
threathened by
BennieHaaknatruns into
policeHaaknathides in amoat

Police findHaaknat in moat

Physical events

Actions

Consequences

Haaknatruns away

Figure 12: the story matched to the intentional action scheme differently

If the story is modelled in this way it does fit the intentional action scheme. However, recall
that another requirement for a story to be plausible was that the individual causal
generalizations on which the causal relations are based must be plausible. If we look at figure
12, it seems that there is a causal relation „X feels threatened by Y  X runs into police → X
hides in a moat‟. Expressed as a generalization, this would read „Someone who feelsthreatened by another person and encounters the police will hide‟. This seems a strange
generalization, because one would expect the person who was threatened to seek help fromthe police. So the story is less plausible because one of its internal causal generalizations is
implausible.
During the case Haaknat said that the reason for the fact that he hid in the moat wasthat he thought the police were looking for him because of the argument with Bennie and that
he did not want to be arrested. The story from figure 11 can be updated with this event, fillingin „Haaknat does not want to be arrested‟ as a psychological state.
Psychological states
Argument
betweenHaaknat andBennieHaaknat feels
threathened by
BennieBennie draws
a knifeHaaknatruns away

Initiating events

Haaknat does
not want tobe arrested

Haaknatruns into
policeHaaknathides in amoat

Police findHaaknat in moat

Physical events

Actions

Consequences

Figure 13: the updated Haaknat story

However, this explanation still is not completely plausible: the fact that it was Bennie
who drew the knife and Haaknat who felt threatened makes it less plausible that Haaknat wasafraid to be arrested. People who are threatened with a knife usually want the police‟s help,
even if they were in a fight themselves. Here, the initiating events are a separate episode with
its own causal structure.
In the above example it can be seen that trying to match the story to the intentional
action scheme requires a careful analysis of the story and even if a story fits the scheme, it isstill important to carefully analyse the causal relations in the story. Matching a story‟s
associated scheme to the intentional action scheme requires one to make the causal relations
between the events explicit so that they can be carefully assessed. This approach to analysing
the plausibility of a story is perhaps closest to the method Crombag et al. and Anderson et al.
propose: make explicit and analyse the generalizations that serve as the basis for the story.
In this section some general features of story schemes and some of the ways in whichstory schemes can be changed have been discussed. The story scheme approach proposed inthis section makes the analysis easier. As was shown in the example in figure 12, theplausibility of causal relations is often dependent on events earlier in the story. So it seems
that often it is not just an individual generalization that is implausible but rather a pattern ofsuccessive events which are connected by generalizations. Instead of taking one causal
generalization and updating by adding further (hidden) conditions, schemes, or chains ofgeneralizations, are added to the model. Take the example in figure 13, where all the eventsin the „initiating events‟ box together with „Haaknat runs into police‟ can be taken as
conditions of a single generalization: „If there is an argument between person X and person Y
and Y draws a knife and X feels threatened by Y and X runs away and X runs into the policethen X will hide‟. However, if these initiating events are modelled as a pattern of events:„argument between person X and person Y – Y draws a knife – X feels threatened by Y – X
runs away – X runs into the police – X will hide‟, it is easier to insert and assess the causal
relations between the different events. If it is modelled as a single causal generalization with

five conditions, the temporal and causal information contained in the „initiating events‟
sub-episode is lost and it is impossible to insert and assess any causal relations between the
different conditions.
5
Story schemes in evidential reasoning
Story schemes can be used in different ways in evidential decision making and crime
investigation. Their use often depends on the particular goals the person using the story
schemes has; a judge or juror can use schemes to analyse a particular story, a lawyer can use
schemes to build a persuasive story and an investigator can use schemes as possible
hypotheses of what happened in a particular case. It is not my intention to provide a fulloverview of the different ways in which story schemes can be used for decision making,persuasion and investigation. The main aim of this section is to briefly discuss some of theuses of the different ways of analysing stories and to provide ideas for future work.
In the decision-making phase, stories put forward by the parties can be criticallyanalysed using schemes, as was illustrated in the previous section. Furthermore, it is also thedecision maker‟s task to see if the prosecutor‟s story fits a story scheme that contains the
charge in the case at hand. In many jurisdictions, an act or a series of acts which arepunishable are defined, often with the required psychological states. Pennington and Hastie
argued that these possible verdicts are much like a story scheme, and that the story should bematched to the verdict category in the same way that a story fits other story schemes. Story
schemes can also be used by the different parties in court to explain „what happened‟ in thecase: a sequence or pattern of events can be given as the cause for an event that is to be
explained. At the end of the previous section it was made clear that giving a pattern or chainof events as an explanation is more natural and provides more possibilities than modellingthe causal relation as a single generalization, giving a conjunction of causes for why a certain
event happened as it did.
In an investigation context, story schemes are important in that they serve as possible
hypotheses for what happened. According to de Poot, Bokhorst, van Koppen and Muller(2004), a criminal case which has to be investigated is often interpreted through different
scenarios, or reconstructions of „what happened‟. When the investigators are faced with acase, different hypothetical scenarios have to be constructed, which can be done by using
story schemes. The fact that story schemes can be used to explain events can also be used in
the analysis of stories. For example, in Haaknat‟s version of the story, the event „argument
between Haaknat and Bennie‟ is not explained. However, we know that the argument was
because of money that Haaknat lent Bennie, so the argument between Haaknat and Bennie
can be explained using the following scheme:
X knows Y

Y needs
money

X has
money

X lends
Y money

Y does not returnthe moneyargument between
X and Y

Figure 14: the ‘argument about money’ story scheme

In this way, the story can be expanded and further analyzed and in this way the search forevidence is guided. For example, if the scheme from figure 14 is used to explain the fact thatHaaknat and Bennie had an argument, there must also be evidence for the fact that „Haaknat
knows Bennie‟. Note that this was also possible in the formalism discussed in section 2.2 but

story schemes allow us to explain events without using abductive inference and thus schemes
allow us to build stories without explicit causal information.
6
Conclusion and future research
From the research on stories in legal reasoning it follows that stories are clearly „necessary
but dangerous‟. Relatively simple patterns of events are easier to handle than complex
argument trees. As Anderson et al. (2005) noted, our stock of knowledge contains not justgeneralizations but also other models of the world and Schank argues that our memories ofpast events are often organized as stories. So stories serve as a useful addition to, for example,
argument trees such as the ones proposed by (Anderson et al. 2005; Wigmore 1931). In theinvestigation phase, stories play more than just a psychological role, because they serve as
scenarios that guide the search for evidence. Whichever role stories are used for, it isimperative that their plausibility and evidential support is constantly tested and analysed.
In my previous work, the analysis and assessment of the plausibility of stories wasdone by attacking generalizations in a causal theory; at the end of section 2 I have shown
another way of analyzing these causal generalizations by exposing hidden conditions or
unpacking the generalizations. However, this way of modelling stories and backgroundknowledge can be complicated as we are dealing with complex causal networks containing
elaborate generalizations with many conditions. Furthermore, stories do often not contain
explicit causal relations between states and events which can be modelled in a causal theory.
In this article, I have proposed another way of modelling background knowledge,
namely as story schemes. This has led to a list of features of story schemes and of the analysisof stories using these schemes:












Story schemes can be modelled as ordered lists of elements, which are events or typesof events, together with the possible (causal or temporal) relations between theseelements.
Story schemes can be used to explain events in the same way as causal theories.
Story schemes range from abstract to specific. In more abstract schemes, theelements of the scheme are general types of states and events (e.g. actions or goals).
In more specific schemes, the elements of the scheme are specific states and events(e.g. X threatens Y with a gun).
Specific story schemes match more abstract story schemes and vice versa to theextent that there are correspondence relations between the elements of the different
schemes. These correspondence relations, which can be expressed as generalizations,have to be plausible for the schemes to match.
If two story schemes match, there is usually also a correspondence between the causal
relations in the different schemes.
Each story has an associated story scheme of which it is an instance (cf. figure 5 and8).
A story fits a story scheme S if its associated story scheme matches S and vice versa.
A story is plausible if it fits the intentional action scheme and if its internal causal
generalizations are plausible
A story is sufficiently detailed if its causal structure is sufficiently detailed.

It must be said that explaining events with simple, less causally connected schemes issomewhat of a blessing in disguise: not having to give a detailed causal theory allows for thequick construction of different scenarios about what happened but care must be taken that the
scenario or the story based on it is sufficiently detailed; the causal structure and the causal
generalizations of the scheme should be sufficiently detailed7.
An important parallel can be drawn between story schemes and argumentation
schemes (Walton 1996), which are schemes that represent stereotypical patterns of humanreasoning through generalizations. Stories and story schemes can be likened to arguments
and argumentation schemes, respectively; an argumentation scheme is a general scheme forarguments of a particular kind just as a story scheme is a general scheme for stories of aparticular kind. In (Walton 1996) a number of argumentation schemes drawn from real world
examples is given. In future research it will also be important to define more types of story
schemes. Furthermore, argumentation schemes also have critical questions which can beused to test the inference and it would be interesting to see if similar questions that can beused to test a story scheme can be defined.
Another subject that has not been discussed in this article is that it is also possible toconstruct and discuss defeasible arguments about the plausibility of stories. The criteria that astory should fit a plausible story scheme and that a story should be supported by evidence
through plausible evidential generalizations are meant to be guidelines for the analysis ofstories. For each individual case, the person performing the analysis has to determine whichstory and what evidence he or she trusts. This decision is also dependent on the task for which
the stories are used; maybe an incomplete story will not convince a judge or juror but in apolice investigation such a story can be a reason to look for other evidence to make the story
complete. While it is impossible to give hard-and-fast rules for which story is the better one,it is possible to argue about the „goodness‟ of the different stories, using the above criteria as
guidelines. These arguments would be on a separate level. For example, arguments could beconstructed for or against a single story (e.g. „your story is not complete‟ or „your story is
implausible‟) or stories could be compared (e.g. „even though my story is not complete, it
covers the evidence much better so my story is the best‟). Verheij and Bex (this volume)
discuss how these kinds of arguments about the plausibility and evidential support can beformulated using argument schemes.
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