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{
"paper_id": "A00-2001",
"header": {
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"date_generated": "2023-01-19T01:12:49.003731Z"
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"title": "Modelling Grounding",
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{
"first": "Colin",
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"last": "Matheson",
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"institution": "University of Edinburgh Edinburgh",
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{
"first": "Massimo",
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"last": "Poesio",
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"affiliation": {
"laboratory": "",
"institution": "University of Edinburgh Edinburgh",
"location": {
"country": "Scotland"
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"email": "massimo.poesio@ed.ac.uk"
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{
"first": "David",
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"last": "Traum",
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"affiliation": {
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"institution": "University of Maryland Maryland",
"location": {
"country": "USA"
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"abstract": "This paper describes an implementation of some key aspects of a theory of dialogue processing whose main concerns are to provide models of GROUNDING and of the role of DISCOURSE OBLIGATIONS in an agent's deliberation processes. Our system uses the TrindiKit dialogue move engine toolkit, which assumes a model of dialogue in which a participan. t's knowledge is characterised in terms of INFORMATION STATES which are subject to various kinds of updating mechanisms.",
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"text": "This paper describes an implementation of some key aspects of a theory of dialogue processing whose main concerns are to provide models of GROUNDING and of the role of DISCOURSE OBLIGATIONS in an agent's deliberation processes. Our system uses the TrindiKit dialogue move engine toolkit, which assumes a model of dialogue in which a participan. t's knowledge is characterised in terms of INFORMATION STATES which are subject to various kinds of updating mechanisms.",
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"section": "Abstract",
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"text": "In this paper we describe a preliminary implementation of a 'middle-level' dialogue management system. The key tasks of a dialogue manager are to update the representation of dialogue on the basis of processed input (generally, but not exclusively, language utterances), and to decide what (if anything) the system should do next. There is a wide range of opinions concerning how these tasks should be performed, and in particular, how the ongoing dialogue state should be represented: e.g., as something very specific to a particular domain, or according to some more general theory of (human or human inspired) dialogue processing. At one extreme, some systems represent only the (typically very rigid) transitions possible in a perceived dialogue for the given task, often using finite states in a transition network to represent the dialogue: examples of this are systems built using Nuance's DialogueBuilder or the CSLU's Rapid Application Prototyper. The other extreme is to build the dialogue processing theory on top of a full model of rational agency (e.g., (Bretier and Sadek, 1996) ). The approach we take here lies in between these two extremes: we use rich representations of information states, but simpler, more dialogue-specific deliberation methods, rather than a deductive reasoner working on the basis of an axiomatic theory of rational agency. We show in this paper that the theory of information states we propose can, nevertheless, be used to give a characterisation of dialogue acts such as those proposed by the Discourse Resource Initiative precise enough to formalise the deliberation process of a dialogue manager in a completely declarative fashion.",
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"text": "(Bretier and Sadek, 1996)",
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"section": "Introduction",
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"text": "Our implementation is based on the approach to dialogue developed in (Traum, 1994; Poesio and Traum, 1997; Poesio and Traum, 1998; . This theory, like other action-based theories of dialogue, views dialogue participation in terms of agents performing dialogue acts, the effects of which are to update the information state of the participants in a dialogue. However, our view of dialogue act effects is closer in some respects to that of (Allwood, 1976; Allwood, 1994) and (Singh, 1998) than to the belief and intention model of (Sadek, 1991; Grosz and Sidner, 1990; Cohen and Levesque, 1990) . Particular emphasis is placed on the social commitments of the dialogue participants (obligations to act and commitments to propositions) without making explicit claims about the actual beliefs and intentions of the participants. Also, heavy emphasis is placed on how dialogue participants socially GROUND (Clark and Wilkes-Gibbs, 1986 ) the information expressed in dialogue: the information state assumed in this theory specifies which information is assumed to be already part of the common ground at a given point, and which part has been introduced, but not yet been established.",
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"section": "Introduction",
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"text": "The rest of this paper is structured as follows. The theory of dialogue underlying the implementation is described in more detail in Section 2. Section 3 describes the implementation itself. Section 4 shows how the system updates its information state while participating in a fairly simple dialogue.",
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"section": "Introduction",
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"text": "One basic assumption underlying this work is that it is useful to analyse dialogues by describing the relevant 'information' that is available to each participant. The notion of INFORMATION STATE (IS) is therefore employed in deciding what the next action should be, and the effects of utterances are described in terms of the changes they bring about in ISs. A particular instantiation of a dialogue manager, from this point of view, consists of a definition of the contents of ISs plus a description of the update processes which map from IS to IS. Updates are typically triggered by 'full' dialogue acts such as assertions or directives, 1 of course, but the theory allows parts of utterances, including individual words and even subparts of words, to be the trigger. The update rules for dialogue acts that we assume here are a simplified version of the formalisations proposed in (Poesio and Traum, 1998; Traum et al., 1999) (henceforth, PTT) .",
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"text": "The main aspects of PTT which have been implemented concern the way discourse obligations are handled and the manner in which dialogue participants interact to add information to the common ground. Obligations are essentially social in nature, and directly characterise spoken dialogue; a typical example of a discourse obligation concerns the relationship between questions and answers. Poesio and Traum follow (Traum and Allen, 1994) in suggesting that the utterance of a question imposes an obligation on the hearer to address the question (e.g., by providing an answer), irrespective of intentions.",
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"text": "As for the process by which common ground is established, or GROUNDING (Clark and Schaefer, 1989; Traum, 1994) , the assumption in PTT is that classical speech act theory is inherently too simplistic in that it ignores the fact that co-operative interaction is essential in discourse; thus, for instance, simply asserting something does not make it become mutually 'known' (part of the common ground). It is actually necessary for the hearer to provide some kind of acknowledgement that the assertion has been received, understood or not understood, accepted or rejected, and so on. Poesio and Traum view the public information state as including both material that has already been grounded, indicated by GND here, and material that hasn't been grounded yet. These components of the information state are updated when GROUNDING ACTS such as acknowledgement are performed. Each new contribution results in a new DIS-COURSE UNIT (DU) being added to the information state (Traum, 1994) and recorded in a list of 'ungrounded discourse units' (UDUS); these DUs can then be subsequently grounded as the result, e.g., of (implicit or explicit) acknowledgements.",
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"text": "Implementing PTT In this section, we describe the details of the implementation. First, in Section 3.1, we describe the TrindiKit tool for building dialogue managers that we used to build our system. In Section 3.2, we describe the information states used in the implementation, an extension and simplification of the ideas from PTT discussed in the previous section. Then, in Section 3.3, we discuss how the information state is updated when dialogue acts are observed. Finally, 1We assume here the DRI classification of dialogue acts (Discourse Resource Initiative, 1997). in Section 3.4, we describe the rules used by the system to adopt intentions and perform its own actions. An extended example of how these mechanisms are used to track and participate in a dialogue is presented in Section 4.",
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"text": "The basis for our implementation is the TrindiKit dialogue move engine toolkit implemented as part of the TRINDI project . The toolkit provides support for developing dialogue systems, focusing on the central dialogue management components.",
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"text": "The system architecture assumed by the TrindiKit is shown in Figure 1 . A prominent feature of this architecture is the information state, which serves as a central 'blackboard' that processing modules can examine (by means of defined CONDITIONS) or change (by means of defined OPERATIONS). The structure of the IS for a particular dialogue system is defined' by the developer who uses the TrindiKit to build that system, on the basis of his/her own theory of dialogue processing; no predefined notion of information state is provided. 2. The toolkit provides a number of abstract data-types such as lists, stacks, and records, along with associated conditions and operations, that can be used to implement the user's theory of information states; other abstract types can also be defined. In addition to this customisable notion of information state, TrindiKit provides a few system variables that can also used for intermodule communication. These include input for the raw observed (language) input, latest_moves which 2In TRINDI we are experimenting with multiple instantiations of three different theories of information state . contains the dialogue moves observed in the most recent turn, latest_speaker, and next_moves, containing the dialogue moves to be performed by the system in the next turn.",
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"text": "A complete system is assumed to consist of several modules interacting via the IS. (See Figure 1 again.) The central component is called the DIA-LOGUE MOVE ENGINE (DME). The DME performs the processing needed to integrate the observed dialogue moves with the IS, and to select new moves for the system to perform. These two functions are encapsulated in the UPDATE and SELECTION submodules of the DME. The update and select modules are specified by means of typed rules, as well as sequencing procedures to determine when to apply the rules. We are here mainly concerned with UP-DATE RULES (urules), which consist of four parts: a name, a type, a list of conditions to check in the information state, and a list of operations to perform on the information state, urules are described in more detail below, in Section 3.3. There are also two modules outside the DME proper, but still crucial to a complete system: INTERPRETATION, which consumes the input and produces a list of dialogue acts in the latest_moves variable (potentially making reference to the current information state), and GENERATION, which produces NL output from the dialogue acts in the next_moves variable. Finally, there is a CONTROL module, that governs the sequencing (or parallel invocation) of the other modules. In this paper we focus on the IS and the DME; our current implementation only uses very simple interpretation and generation components.",
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"text": "In this section we discuss the information state used in the current implementation. The main difference between the implemented IS and the theoretical proposal in (Poesio and Traum, 1998) is that in the implementation the information state is partitioned in fields, each containing information of different types, whereas in the theoretical version the information state is a single repository of facts (a DISCOURSE REPRESENTATION STRUCTURE). Other differences are discussed below. An example IS with some fields filled is shown in Figure 2 ; this is the IS which results from the second utterance in the example dialogue discussed in Section 4, A route please. 3",
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"text": "The IS in Figure 2 is a record with two main parts, W and C. The first of these represents the system's (Wizard) view of his own mental state and of the (semi-)public information discussed in the dialogue; the second, his view of the user's (Caller) information state. This second part is needed to 3All diagrams in this paper are automatically generated from TrindiKit system internal representations and displayed using the Thistle dialogue editor (Calder, 1998 1 /,,,,o_,..,,,.,( w.:,,.-, grounded; as we are not concerned with this problem here, we will ignore C in what follows. w contains information on the grounded material (GND), on the ungrounded information (UDUS, PDU and CDU), and on W's intentions (INT) . GND contains the information that has already been grounded; the other fields contain information about the contributions still to be grounded. As noticed above, in PTT it is assumed that for each new utterance, a new DU is created and added to the IS. The current implementation differs from the full theory in that only two DUs are retained at each point; the current DU (CDU) and the previous DU (PDU). The CDU contains the information in the latest contribution, while the PDU contains information from the penultimate contribution. Information is moved from PDU to GND as a result of an ack (acknowledgement) dialogue act (see below.)",
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"text": "The DUs and the GND field contain four fields, representing obligations (OBL), the dialogue history (DH), propositions to which agents are socially committed (scP), and conditional updates (COND). The value of OBL is a list of action types: actions that agents are obliged to perform. An action type is specified by a PREDICATE, a DIALOGUE PARTICI-PANT, and a list of ARGUMENTS. The value of see is a list of a particular type of mental states, social commitments of agents to propositions. 4 These are specified by a DIALOGUE PARTICIPANT, and a PROPOSITION. Finally, the elements in DH are dia-4SCPs play much the same role in PTT as do beliefs in many BDI accounts of speech acts. logue actions, which are instances of dialogue action types. A dialogue action is specified by an action type, a dialogue act id, and a confidence level CONF (the confidence that an agent has that that dialogue act has been observed).",
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"text": "The situation in Figure 2 is the result of updates to the IS caused by utterance [2] in the dialogue in (6), which is assumed to generate a direct act as well as an assert act and an answer act. 5 That utterance is also assumed to contain an implicit acknowledgement of the original question; this understanding act has resulted in the contents of DU2 being grounded (and subsequently merged with GND), as discussed below.",
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"text": "GND.OBL in Figure 2 includes two obligations. The first is an obligation on W to perform an understanding act (the predicate is understandingAct, the participant is W, and there is just one argument, DU3, which identifies the DU in CDU by referring to its ID). The second obligation is an obligation on C to address conversational act CA2; this ID points to the appropriate info_request in the DH list by means of the ID number. Obligations are specified in CDU and PDU, as well. Those in PDU are simply a subset of those in GND, since at point in the update process shown in Figure 2 this field contains information that has already been grounded (note that DU2 is not in UDUS anymore); but CDU contains obligations that have not been grounded yetin particular, the obligation on W to address CA6.",
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"text": "GND.DH in this IS contains a list of dialogue actions whose occurrence has already been grounded: the info_request performed by utterance 1, with argument a question, 6 and the implicit acknowledge performed by utterance 2. 7 The DH field in CDU contains dialogue acts performed by utterance 2 that do need to be grounded: a directive by C to W to perform an action of type giveroute, and an assert by C of the proposition want(C, route), by which C provides an answer to the previous info_request CA2.",
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"text": "The COND field in CDU contains a conditional update resulting from the directive performed by that utterance. The idea is that directives do not immediately lead to obligations to perform the mentioned action: instead (in addition to an obligation to address the action with some sort of response), their effect is to add to the common ground the information that if the directive is accepted by the addressee, SThe fact that the utterance of a route please constitutes an answer is explicitly assumed; however, it should be possible to derive this information automatically (perhaps along the lines suggested by Kreutel (Kreutel, 1998) 7We assume here, as in (Traum, 1994) and (Poesio and Traum, 1998) , that understanding acts do not have to be grounded themselves, which would result in a infinite regress. then he or she has the obligation to perform the action type requested. (In this case, to give a route to C.)",
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"text": "We are now in a position to examine the update mechanisms which are performed when new dialogue acts are recognised. When a dialogue participant takes a turn and produces an utterance, the interpretation module sets the system variable latest_moves to contain a representation of the dialogue acts performed with the utterance. The updating procedure then uses update rules to modify the IS on the basis of the contents of latest_moves and of the previous IS. The basic procedure is described in (1) below, s",
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"text": "(1) 1. Create a new DU and push it on top of UDUs.",
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"text": "2. Perform updates on the basis of backwards grounding acts.",
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"text": ". If any other type of act is observed, record it in the dialogue history in CDU and apply the update rules for this kind of act 4. Apply update rules to all parts of the IS which contain newly added acts.",
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"text": "The first step involves moving the contents of CDU to PDU (losing direct access to the former PDU contents) and putting in CDU a new empty DU with a new identifier. The second and third steps deal explicitly with the contents of latest.moves, applying one urule (of possibly a larger set) for each act in latest_moves. The relevant effects for each act are summarised in 2 SSee for different versions of this update procedure used for slightly different versions of the theory.",
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"text": "(2) act ID:2, accept (DP, ID2) effect accomplished via rule resolution act ID:2, ack(DP, DU1) effect peRec(w.Gnd,w.pdu.tognd) effect remove(DU1,UDUS) act ID:2, agree(DP, ID2) effect push(scP,scp(DP,P(ID2))) act ID:2, answer(DP,ID2,ID3) effect push(scP,ans(DP, Q(ID2),P(ID2))) act ID:2, assert (DP,PROP) effect push(scP,sep(DP, PROP)) effect push (COND,accept (o(DP),ID)-+ scp(o(DP),PROP)) act ID:I, assert(DP,PROP) effect push (COND,accept (o(DP),ID)-~ scp(o(DP),PROP)) act ID:2, check(DP,PROP) effect push(OSL,address(o(DP),ID)) effect push(COND,agree(o(DP),ID) --~ scp(DP, PROP)) act ID:2, direct (DP, Act) effect push(OBL,address(o(DP),ID)) effect push(CONI),accept (o(DP),ID) -~ obl(o(DP),Act)) act ID:2, info_request (DP, Q) effect push(osL,address(o(DP),ID))",
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"text": "The ack act is the only backward grounding act implemented at the moment. The main effect of an ack is to merge the information in the acknowledged DU (assumed to be PDU) into GND, also removing this DU from UDUS. Unlike the other acts described below, ack acts are recorded directly into GND.DH, rather than into CDU.TOGND.DH.",
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"text": "All of the other updates are performed in the third step of the procedure in (1). The only effect of accept acts is to enable the conditional rules which are part of the effect of assert and direct, leading to social commitments and obligations, respectively. agree acts also trigger conditional rules introduced by check; in addition, they result in the agent being socially committed to the proposition introduced by the act with which the agent agrees. Performing an answer to question ID2 by asserting proposition P(ID3) commits the dialogue participant to the proposition that P(ID3) is indeed an answer to Q(ID2).",
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"text": "The two rules for assert are where the confidence levels are actually used, to implement a simple verification strategy. The idea is that the system only assumes that the user is committed to the asserted proposition when a confidence level of 2 is observed, while some asserts are assumed not to have been sufficiently well understood, and are only assigned a confidence level 1. This leads the system to perform a check, as we will see shortly.",
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"text": "The next three update rules, for check, direct, and info_req, all impose an obligation on the other dialogue participant to address the dialogue act. In addition, the direct rule introduces a conditional act: acceptance of the directive will impose an obligation on the hearer to act on its contents.",
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"text": "In addition, all FORWARD ACTS 9 in the DRI scheme (Discourse Resource Initiative, 1997) impose an obligation to perform an understanding act (e.g., an acknowledgement):",
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"text": "(3) 1 act effect ID:c, forward-looking-act (DP) push (OBL,u-act (o(DP) ,CDU.id)) I",
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"text": "The internal urules implementing the updates in (2) have the format shown in (4), which is the urule for info_request. As noted above, these rules have four parts; a name, a type, a list of conditions, and a list of effects. The conditions in (4) state that there must be a move in latest_moves whose predicate is inforeq. The effects l\u00b0 state that the move should be recorded in the dialogue history in CDU, that an obligation to address the request should be pushed into OBL in CDU, and that the requirement for an understanding act by W should be pushed directly into the list in W.GND.",
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"text": "The fourth and final step of the algorithm cycles through the updating process in case recently added facts have further implications. For instance, when an action has been performed that matches the antecedent of a rule in COND, the consequent is established. Likewise, when an action is performed it releases any obligations to perform that action. Thus, accept, answer, and agree are all ways of releasing an obligation to address, since these are all appropriate backward looking actions. Similarly, an agent will drop intentions to perform actions it has already (successfully) performed.",
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"text": "We assume, in common with BDI-approaches to agency (e.g., (Bratman et al., 1988) ) that intentions 9Forward acts include assert, check, direct, and info_request.",
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"start": 58,
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"text": "l\u00b0The ID and HID values simply contain numbers identifying the discourse units and conversational acts.",
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"text": "are the primary mental attitude leading to an agent's actions. The main issues to explain then become how such intentions are adopted given the rest of the information state, and how an agent gets from intentions to actual performance.",
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"text": "For the latter question, we take a fairly simplistic approach here: all the intentions to perform dialogue acts are simply transferred to the next_moves system variable, with the assumption that the generation module can realise all of them as a single utterance. A more sophisticated approach would be to weight the importance of (immediate) realisation of sets of intentions and compare this to the likelihood that particular utterances will achieve these effects at minimal cost, and choose accordingly. We leave this for future work (see (Traum and Dillenbourg, 1998) for some preliminary ideas along these lines), concentrating here on the first issue -how the system adopts intentions to perform dialogue acts from other aspects of the mental state.",
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"start": 542,
"end": 571,
"text": "(Traum and Dillenbourg, 1998)",
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"text": "The current system takes the following factors into account:",
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"text": "\u2022 obligations (to perform understanding acts, to address previous dialogue acts, to perform other actions)",
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"sec_num": "3.4"
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"text": "\u2022 potential obligations (that would result if another act were performed, as represented in the COND field)",
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"sec_num": "3.4"
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"text": "\u2022 insufficiently understood dialogue acts (with a 1 confidence level in CDU.DH)",
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"sec_num": "3.4"
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"text": "\u2022 intentions to perform complex acts",
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"text": "The current deliberation process assumes maximal cooperativity, in that the system always chooses to meet its obligations whenever possible, and also chooses to provide a maximally helpful response when possible. Thus, when obliged to address a previous dialogue act such as a question or directive, it will choose to actually return the answer or perform the action, if possible, rather than reject or negotiate such a performance, which would also be acting in accordance with the obligations (see (Kreutel, 1998) on how acts might be rejected).",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
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"sec_num": "3.4"
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"text": "In the current implementation, the following rules are used to adopt new intentions (i.e., to update the INT field):",
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"text": "(5) 1. add an intention to acknowledge(W,CDU), given an obligation to perform a u-act, if everything in CDU is sufficiently understood (i.e., to level 2); 2. add an intention to accept a directive or answer a question as the result of an obligation to address a dialogue act; 3. add an intention to perform an action if COND contains a conditional that will establish an obligation to perform the action, and the antecedent of this conditional is another action that is already intended. (This anticipatory planning allows the obligation to be discharged at the same time it is invoked, e.g., without giving an intermediate acceptance of an directive.)",
"cite_spans": [],
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"sec_num": "3.4"
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"text": "4. add an intention to perform a (dialogue) action motivated by the intention to perform the current task. In the case of the Autoroute domain, we have two cases: the system may decide (a) to check any dialogue acts in CDU at confidence level 1, which contain information needed to discharge the intention to give a route; or (b) to perform a question asking about a new piece of information that has not been established (this is decided by inspecting GND.SCP and CDU.SCP). For example, it may decide to ask about the starting point, the time of departure, etc.",
"cite_spans": [],
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"sec_num": "3.4"
},
{
"text": "4 Extended Example In this section, we discuss more examples of how the information state changes as a result of processing and performing dialogue acts. It is useful to do this by looking briefly at a typical Autoroute dialogue, shown in (6). 11 Our implementation can process this sort of dialogue using very simple interpretation and generation routines that provide the dialogue acts in latest_moves from the text strings, and produce W's output text from the dialogue acts which the system places in next_moves. 6 We assume that before the dialogue starts, W has the intention to ask C what kind of help is required, liThe interchanges have been cleaned up to some extent here, mainly by removing pauses and hesitations. been assumed. Current and future work is directed towards measuring the theory against more challenging data to test its validity; cases where grounding is less automatic are an obvious source of such tests, and we have identified a few relevant problem cases in the Autoroute dialogues. We do claim, however, that the implementation as it stands validates a number of key aspects of the theory and provides a good basis for future work in dialogue modelling.",
"cite_spans": [],
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],
"back_matter": [
{
"text": "The TRINDI (Task Oriented Instructional Dialogue) project is supported by the Telematics Applications Programme, Language Engineering Project LE4-8314. Massimo Poesio is supported by an EP-SRC Advanced Research Fellowship.",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Acknowledgments",
"sec_num": null
},
{
"text": "and that C has the intention to find a route. We also assume that W has the turn, and that the presence of the how can I help intention triggers an utterance directly. After C's agreement in [6], the deliberation routine is able to move past discussion of the starting point, and add an intention to ask about the next piece of information, the destination. This leads to producing utterance [7], which also implicitly acknowledges [6], after which C's agreement is grounded, leading to the IS shown in Figure 5 . Note that the list in W.GND.SCP in Figure 5 indicates that both C and W are committed to the proposition that the starting place is Malvern.",
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{
"start": 503,
"end": 511,
"text": "Figure 5",
"ref_id": null
},
{
"start": 549,
"end": 557,
"text": "Figure 5",
"ref_id": null
}
],
"eq_spans": [],
"section": "annex",
"sec_num": null
},
{
"text": "It has only been possible here to introduce the basic concerns of the PTT account of dialogue modelling and to pick out one or two illustrative examples to highlight the implementational approach which has",
"cite_spans": [],
"ref_spans": [],
"eq_spans": [],
"section": "Conclusions",
"sec_num": "5"
}
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"ref_entries": {
"FIGREF0": {
"uris": null,
"text": "Figure 1: TrindiKit Architecture",
"num": null,
"type_str": "figure"
},
"FIGREF1": {
"uris": null,
"text": "*~,~,d~(W.bU3)/ JI lINT: <letrome(C)>] J Structure of Information States model misunderstandings arising from the dialogue participants having differing views on what has been",
"num": null,
"type_str": "figure"
},
"FIGREF2": {
"uris": null,
"text": "=uxe( doZnfoR, q. rulet~.S, [ hearer(DP), latest_moves: in(Hove}, Move:valEec(pred,inforeq) ], [ incr_set(update_cycles,_), incr_set (next.dh_id, HID), next _du_name (ID), pushRec (w'cdu'tognd'dh, record ( [atype=Move, c level=2, id=HID ])), pushRec (e'cdu~tosnd'obl, record ( [pred~address, dp=DP,",
"num": null,
"type_str": "figure"
},
"TABREF0": {
"content": "<table><tr><td/><td colspan=\"3\">r [OBL: ~lddre~(C,CA2 ) ] understandingAct( W,DU3 )\\ ]</td><td>1 /</td><td>~1 //</td></tr><tr><td colspan=\"2\">~.. /..</td><td colspan=\"2\">/CAS:C2 ,~..,~g.(C.DU2)</td><td>\\/</td><td>II</td></tr><tr><td colspan=\"3\">..... / .... \\c^:: / sc : &lt; \" [COND: &lt; &gt;</td><td/><td>'// ! J</td><td>II H H</td></tr><tr><td colspan=\"2\">UDUS: &lt;DU3&gt;</td><td/><td/><td/><td>H</td></tr><tr><td/><td>[</td><td colspan=\"2\">[OBL: &lt;,ddri~z(C.CA2 ) &gt;</td><td>]]</td><td>H</td></tr><tr><td/><td/><td>DH:</td><td colspan=\"2\">&lt;CA2: C2. into requi~t( W.?help fore1 ) :&gt;</td></tr><tr><td>/ : |</td><td>/ LID:</td><td colspan=\"2\">LCOND: &lt; &gt; DU2</td><td colspan=\"2\">J/ If J II</td></tr><tr><td>/ /</td><td>[ /</td><td>/</td><td colspan=\"2\">/CA5: C2. dil c,(C ivemule(W) ) \\</td><td>lilt //H</td></tr><tr><td>/ ko,, I /</td><td>/ / [</td><td colspan=\"4\">/DH: LCOND: &lt;IICIpt(W.CA6)-&gt; obl(W~iveroutc(W))&gt;J III (CAS: C2. a,swer( C.CA2.CA4 ) ) //11 //11 IIII</td></tr><tr><td>/</td><td>LID:</td><td>DU3</td><td/><td/><td>JII</td></tr></table>",
"text": "). Some have been subsequently edited for brevity and clarity.",
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"num": null,
"type_str": "table"
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