Contents of 'Using Enthymemes in an Inquiry Dialogue System' (2008), by Eilzabeth Black and Anthony Hunter
... Here we investigate the use of enthymemes in inquiry dialogues. For this, we propose a generative inquiry dialogue system and show how, in this dialogue system, enthymemes can be managed by the agents involved, and how common knowledge can evolve through dialogue.
Introduction
... Here, we adapt and integrate [previous] proposals in order to define a new framework for generating inquiry dialogues that use enthymemes. The agents involved can send and receive enthymemes, they can query the other agent if they do not understand an enthymeme they have received, and they can update their perception of what can be used as common knowledge based on the information exchanged during the dialogue.
Logical Arguments
Enthymemes
Representing Dialogues
Generating Dialogues
Properties of Dialogue System
Conclusions
Showing posts with label inquiry. Show all posts
Showing posts with label inquiry. Show all posts
Tuesday, 11 March 2008
Wednesday, 29 August 2007
Example Dialogue (Safe Car)
Taken from 'Dialogue Games for Ontological Commitment' (2003), Robbert-Jan Beun and M. van Eijk
We give an example of a dialogue (somewhat adorned in natural language) that is generated by the rules [presented in the paper]:
A1: Is this a safe car?
A2's ontology defines the non-basic concept 'safety' in terms of 'having airbags' and 'having a good crash test'. According to this interpretation the car is indeed believed to be safe, but since A2 does not know the meaning is shared it responds... :
A2: Yes, it has air bags and a good crash test.
This response is pushed on the stack of A1. Agent A1, however, has a different view on 'safety of cars', and it manifests this discrepency by responding ... :
A1: To my opinion, a safe car would also have traction control.
Agent A2 now knows A1's interpretation of 'safety' ... and since it believes that this particular car does not have traction control it gives the following answer to the initial question ... :
A2: Mhm, if safety also amounts to having traction control then this car is not safe.
This response is pushed on the stack of A1. Agent A1 has received an acceptable answer to its question and ends the dialogue ... :
A1: OK, thank you.
Note that if in the second turn, A2 would not have manifested its interpretation of 'safety', the ontological discrepency would have remained unnoticed, possibly leading A1 to draw incorrect conclusions from the answer.
We give an example of a dialogue (somewhat adorned in natural language) that is generated by the rules [presented in the paper]:
A1: Is this a safe car?
A2's ontology defines the non-basic concept 'safety' in terms of 'having airbags' and 'having a good crash test'. According to this interpretation the car is indeed believed to be safe, but since A2 does not know the meaning is shared it responds... :
A2: Yes, it has air bags and a good crash test.
This response is pushed on the stack of A1. Agent A1, however, has a different view on 'safety of cars', and it manifests this discrepency by responding ... :
A1: To my opinion, a safe car would also have traction control.
Agent A2 now knows A1's interpretation of 'safety' ... and since it believes that this particular car does not have traction control it gives the following answer to the initial question ... :
A2: Mhm, if safety also amounts to having traction control then this car is not safe.
This response is pushed on the stack of A1. Agent A1 has received an acceptable answer to its question and ends the dialogue ... :
A1: OK, thank you.
Note that if in the second turn, A2 would not have manifested its interpretation of 'safety', the ontological discrepency would have remained unnoticed, possibly leading A1 to draw incorrect conclusions from the answer.
Saturday, 31 March 2007
15.5-15.7, A Generative Inquiry Dialogue System
Notes taken from ‘A Generative Inquiry Dialogue System’ (2007), by Elizabeth Black and Anthony Hunter
5, Soundness and Completeness
5.1, The argument inquiry outcome of a dialogue is a function… if D is a well-formed argument inquiry dialogue with participants x1 and x2, then… (given D the outcome is the set of all arguments that can be constructed from the union of the commitment stores and whose claims are in the question store).
… The benchmark that we compare the outcome of the dialogue with is the set of arguments that can be constructed from the union of the two agents’ beliefs. So this benchmark is, in a sense, the ‘ideal situation’ where there are clearly no constraints on the sharing of beliefs.
5.2, Let D be a well-formed argument inquiry dialogue with participants x1 and x2. We say that D is sound if and only if… (when the outcome of the dialogue includes an argument, then that same argument can be constructed from the union of the two participating agents’ beliefs).
(Theorem 5.1) If D is a well-formed argument inquiry dialogue with participants x1 and x2, then D is sound. Proof: …
5.3, Let D be a well-formed argument inquiry dialogue with participants x1 and x2. We say that D is complete iff… (if the dialogue terminates at t and it is possible to construct an argument for a literal in the question store from the union of the two participating agents’ beliefs, then that argument will be in the outcome of the dialogue at t.)
(Theorem 5.2) If D is a well-formed argument inquiry dialogue with participants x1 and x2, then D is complete. Proof: …
6, Future work…
… We would like to allow more than two agents to take part in an argument inquiry dialogue…
We currently assume that an agent’s belief base does not change during a dialogue, and would like to consider the implication of dropping this assumption…
We would also like to further explore the benchmark which we compare our dialogue outcomes to…
… We would like to further investigate the utility of argument inquiry dialogues when embedded in dialogues of different types.
7, Conclusions…
5, Soundness and Completeness
5.1, The argument inquiry outcome of a dialogue is a function… if D is a well-formed argument inquiry dialogue with participants x1 and x2, then… (given D the outcome is the set of all arguments that can be constructed from the union of the commitment stores and whose claims are in the question store).
… The benchmark that we compare the outcome of the dialogue with is the set of arguments that can be constructed from the union of the two agents’ beliefs. So this benchmark is, in a sense, the ‘ideal situation’ where there are clearly no constraints on the sharing of beliefs.
5.2, Let D be a well-formed argument inquiry dialogue with participants x1 and x2. We say that D is sound if and only if… (when the outcome of the dialogue includes an argument, then that same argument can be constructed from the union of the two participating agents’ beliefs).
(Theorem 5.1) If D is a well-formed argument inquiry dialogue with participants x1 and x2, then D is sound. Proof: …
5.3, Let D be a well-formed argument inquiry dialogue with participants x1 and x2. We say that D is complete iff… (if the dialogue terminates at t and it is possible to construct an argument for a literal in the question store from the union of the two participating agents’ beliefs, then that argument will be in the outcome of the dialogue at t.)
(Theorem 5.2) If D is a well-formed argument inquiry dialogue with participants x1 and x2, then D is complete. Proof: …
6, Future work…
… We would like to allow more than two agents to take part in an argument inquiry dialogue…
We currently assume that an agent’s belief base does not change during a dialogue, and would like to consider the implication of dropping this assumption…
We would also like to further explore the benchmark which we compare our dialogue outcomes to…
… We would like to further investigate the utility of argument inquiry dialogues when embedded in dialogues of different types.
7, Conclusions…
15.4, A Generative Inquiry Dialogue System
Notes taken from ‘A Generative Inquiry Dialogue System’ (2007), by Elizabeth Black and Anthony Hunter
4, Dialogue System
The communicative acts in a dialogue are called moves. We assume that there are always exactly two agents (participants) taking part in a dialogue… Each participant takes its turn to make a move to the other participant…
A move in our system is of the form (Agent, Act, Content)… e.g. (x, ‘open’, belief), (x, ‘assert’, (support, conclusion)), (x, ‘close’, belief)…
4.1, A dialogue… is a sequence of moves of the form… (The first move of a dialogue… must always be an open move…, every move of the dialogue must be made to a participant of the dialogue…, and the agents take it in turns to receive moves…)
4.2, (Terminology that allows us to talk about the relationship between two dialogues: ‘Sub-dialogue of’…, ‘top-level dialogue’…, ‘top-dialogue of’…, and ‘extends’…)
4.3, Let D be a dialogue with participants x1 and x2 such that topic(D) = gamma. We say that m(s)… is a matched-closed for D iff m(s-1) = (P, close, gamma) and m(s) = (~P, close, gamma).
So a matched-close will terminate a dialogue D but only if D has not already terminated and any sub-dialogues that are embedded within D have already terminated.
4.4, Let D be a dialogue. D terminates at t iff the following conditions hold…
4.5, The current dialogue is… (the innermost dialogue that has not yet terminated).
We adopt the standard approach of associating a commitment store with each agent participating in a dialogue. A commitment store is a set of beliefs that the agent has asserted so far in the course of the dialogue. As commitment stores consist of things that the agent has already publicly declared, its contents are visible to the other agent participating in the dialogue. For this reason, when constructing an argument, an agent may make use of not only its own beliefs but also those from the other agent’s commitment store.
4.6, A commitment store associated with an agent… is a set of beliefs.
An agent’s commitment store grows monotonically over time. If an agent makes a move asserting an argument, every element of the support is added to the agent’s commitment store. This is the only time the commitment store is updated.
4.7, Commitment store update…
… when an argument inquiry dialogue with topic ‘alpha1 ^ … ^ alphaN -> phi’ is opened, a question store associated with that dialogue is created whose contents are {alpha1, …, alphaN}. Throughout the dialogue the participant agents will both try to provide arguments for the literals in the question store. This may lead them to open further nested argument inquiry dialogues that have a topic a rule consequent is a literal in the question store.
4.8… a question store… is a finite set of literals such that…
A protocol is a function that returns the set of moves that are legal for an agent to make at a particular point in a particular type of dialogue…
4.9, The argument inquiry protocol is a function (that takes the top-level dialogue that the agents are participating in and the identifier of the agent whose turn it is to move, and returns the set of legal moves that the agent can make)…
(An agent can only assert an argument or open a rule for a conclusion that is in the current Question Store, and such that the move has not been made by either agent at an earlier timepoint in the dialogue.)
Note that it is straightforward to check conformance with the protocol as the protocol only refers to public elements of the dialogue.
… a specific strategy function… allows an agent to select exactly one legal move to make at each timepoint in an argument inquiry dialogue. A strategy is personal to an agent and the move that it returns depends on the agent’s private beliefs. The argument inquiry strategy states that if there are any legal moves that assert an argument that can be constructed by the agent (by means of its belief base and the other agent’s commitment store) then a single one of those moves is selected…, else if there are any legal open moves with a defeasible rule as their content that is in the agent’s beliefs then a single one of these moves is selected… If there are no such moves then a close move is made.
4.10… The function pickO returns the chosen open move…
4.11… The function pickA returns the chosen assert move…
4.12, The argument inquiry strategy is a function (that takes the top-level dialogue that the agents are participating in and the identifier of the agent whose turn it is to move, and returns exactly one of the legal moves)…
Note that a top-level argument inquiry dialogue will always have a defeasible fact as its topic, but each of its sub-dialogues will always have a defeasible rule as its topic.
4.13, D is a well-formed argument inquiry dialogue iff… (D does not continue after it has terminated and is generated by the argument inquiry strategy).
… Note that we assume some higher-level planning component that guides the agent when deciding whether to enter into a dialogue, who this dialogue should be with and on what topic, i.e. that makes the decision to make the move m1.
4, Dialogue System
The communicative acts in a dialogue are called moves. We assume that there are always exactly two agents (participants) taking part in a dialogue… Each participant takes its turn to make a move to the other participant…
A move in our system is of the form (Agent, Act, Content)… e.g. (x, ‘open’, belief), (x, ‘assert’, (support, conclusion)), (x, ‘close’, belief)…
4.1, A dialogue… is a sequence of moves of the form… (The first move of a dialogue… must always be an open move…, every move of the dialogue must be made to a participant of the dialogue…, and the agents take it in turns to receive moves…)
4.2, (Terminology that allows us to talk about the relationship between two dialogues: ‘Sub-dialogue of’…, ‘top-level dialogue’…, ‘top-dialogue of’…, and ‘extends’…)
4.3, Let D be a dialogue with participants x1 and x2 such that topic(D) = gamma. We say that m(s)… is a matched-closed for D iff m(s-1) = (P, close, gamma) and m(s) = (~P, close, gamma).
So a matched-close will terminate a dialogue D but only if D has not already terminated and any sub-dialogues that are embedded within D have already terminated.
4.4, Let D be a dialogue. D terminates at t iff the following conditions hold…
4.5, The current dialogue is… (the innermost dialogue that has not yet terminated).
We adopt the standard approach of associating a commitment store with each agent participating in a dialogue. A commitment store is a set of beliefs that the agent has asserted so far in the course of the dialogue. As commitment stores consist of things that the agent has already publicly declared, its contents are visible to the other agent participating in the dialogue. For this reason, when constructing an argument, an agent may make use of not only its own beliefs but also those from the other agent’s commitment store.
4.6, A commitment store associated with an agent… is a set of beliefs.
An agent’s commitment store grows monotonically over time. If an agent makes a move asserting an argument, every element of the support is added to the agent’s commitment store. This is the only time the commitment store is updated.
4.7, Commitment store update…
… when an argument inquiry dialogue with topic ‘alpha1 ^ … ^ alphaN -> phi’ is opened, a question store associated with that dialogue is created whose contents are {alpha1, …, alphaN}. Throughout the dialogue the participant agents will both try to provide arguments for the literals in the question store. This may lead them to open further nested argument inquiry dialogues that have a topic a rule consequent is a literal in the question store.
4.8… a question store… is a finite set of literals such that…
A protocol is a function that returns the set of moves that are legal for an agent to make at a particular point in a particular type of dialogue…
4.9, The argument inquiry protocol is a function (that takes the top-level dialogue that the agents are participating in and the identifier of the agent whose turn it is to move, and returns the set of legal moves that the agent can make)…
(An agent can only assert an argument or open a rule for a conclusion that is in the current Question Store, and such that the move has not been made by either agent at an earlier timepoint in the dialogue.)
Note that it is straightforward to check conformance with the protocol as the protocol only refers to public elements of the dialogue.
… a specific strategy function… allows an agent to select exactly one legal move to make at each timepoint in an argument inquiry dialogue. A strategy is personal to an agent and the move that it returns depends on the agent’s private beliefs. The argument inquiry strategy states that if there are any legal moves that assert an argument that can be constructed by the agent (by means of its belief base and the other agent’s commitment store) then a single one of those moves is selected…, else if there are any legal open moves with a defeasible rule as their content that is in the agent’s beliefs then a single one of these moves is selected… If there are no such moves then a close move is made.
4.10… The function pickO returns the chosen open move…
4.11… The function pickA returns the chosen assert move…
4.12, The argument inquiry strategy is a function (that takes the top-level dialogue that the agents are participating in and the identifier of the agent whose turn it is to move, and returns exactly one of the legal moves)…
Note that a top-level argument inquiry dialogue will always have a defeasible fact as its topic, but each of its sub-dialogues will always have a defeasible rule as its topic.
4.13, D is a well-formed argument inquiry dialogue iff… (D does not continue after it has terminated and is generated by the argument inquiry strategy).
… Note that we assume some higher-level planning component that guides the agent when deciding whether to enter into a dialogue, who this dialogue should be with and on what topic, i.e. that makes the decision to make the move m1.
15.1-15.3, A Generative Inquiry Dialogue System
Notes taken from ‘A Generative Inquiry Dialogue System’ (2007), by Elizabeth Black and Anthony Hunter
“… We focus on inquiry dialogues that allow two agents to share knowledge in order to construct an argument for a specific claim…”
1, Introduction
Dialogue games are now a common approach to defining communicative agent behaviour, especially when this behaviour is argumentation-based… Dialogue games are normally made up of a set of communicative acts called moves, a set of rules that state which moves it is legal to make at any point in a dialogue (the protocol), a set of rules that define the effect of making a move, and a set of rules that determine when a dialogue terminates. Most of the work so far has looked at modelling different types of dialogue in the Walton and Krabbe typology… here we provide a generative system.
... A key contribution of this work is that we not only provide a protocol for modelling inquiry dialogues but we also provide a specific strategy to be followed, making this system sufficient to also generate inquiry dialogues… and this allows us to consider soundness and completeness properties of our system.
2, Motivation
Our work has been motivated by the medical domain. Argumentation allows us to deal with the incomplete, inconsistent and uncertain knowledge that is characteristic of medical knowledge. There are often many different healthcare professionals involved in the care of a patient, each of whom has a particular type of specialised knowledge and who must cooperate in order to provide the best possible care for the patient…
Inquiry dialogues are a type of knowledge that would be of particular use in the healthcare domain, where it is often the case that people have distinct types of knowledge and so need to interact with others in order to have all the information necessary to make a decision…
… We compare the outcome of our dialogues with the outcome that would be arrived at by a single agent that has at its beliefs the union of both the agents participating in the dialogues beliefs. This is, in some sense, the ideal situation, where there are no constraints on the sharing of beliefs.
3, Knowledge Representation and Arguments
We adapt Garcia and Simari’s Defeasible Logic Programming (DeLP)… for representing each agent’s beliefs…
The presentation in this section differs slightly from that in (Garcia and Simari’s DeLP)… as (they) assume a set of strict rules, which we assume to be empty, and they assume facts to be non-defeasible. We assume that all knowledge is defeasible due to the nature of medical knowledge, which is constantly expanding…
3.1, A defeasible rule is denoted 'alpha1 ^ … ^ alphaN -> alpha0' where alphai is a literal… A defeasible fact is denoted 'alpha' where alpha is a literal. A belief is either a defeasible rule of a defeasible fact.
3.2, A belief base associated with an agent x is a finite set…
3.3… A defeasible derivation of (a literal) ‘alpha’ from (a set of beliefs)… is a finite sequence alpha1, alpha2, …, alphaN of literals such that alphaN is alpha and each literal… is in the sequence because…
3.4, An argument constructed from a set of, possibly inconsistent, beliefs… is a minimally consistent set from which the claim can be defeasibly derived…
“… We focus on inquiry dialogues that allow two agents to share knowledge in order to construct an argument for a specific claim…”
1, Introduction
Dialogue games are now a common approach to defining communicative agent behaviour, especially when this behaviour is argumentation-based… Dialogue games are normally made up of a set of communicative acts called moves, a set of rules that state which moves it is legal to make at any point in a dialogue (the protocol), a set of rules that define the effect of making a move, and a set of rules that determine when a dialogue terminates. Most of the work so far has looked at modelling different types of dialogue in the Walton and Krabbe typology… here we provide a generative system.
... A key contribution of this work is that we not only provide a protocol for modelling inquiry dialogues but we also provide a specific strategy to be followed, making this system sufficient to also generate inquiry dialogues… and this allows us to consider soundness and completeness properties of our system.
2, Motivation
Our work has been motivated by the medical domain. Argumentation allows us to deal with the incomplete, inconsistent and uncertain knowledge that is characteristic of medical knowledge. There are often many different healthcare professionals involved in the care of a patient, each of whom has a particular type of specialised knowledge and who must cooperate in order to provide the best possible care for the patient…
Inquiry dialogues are a type of knowledge that would be of particular use in the healthcare domain, where it is often the case that people have distinct types of knowledge and so need to interact with others in order to have all the information necessary to make a decision…
… We compare the outcome of our dialogues with the outcome that would be arrived at by a single agent that has at its beliefs the union of both the agents participating in the dialogues beliefs. This is, in some sense, the ideal situation, where there are no constraints on the sharing of beliefs.
3, Knowledge Representation and Arguments
We adapt Garcia and Simari’s Defeasible Logic Programming (DeLP)… for representing each agent’s beliefs…
The presentation in this section differs slightly from that in (Garcia and Simari’s DeLP)… as (they) assume a set of strict rules, which we assume to be empty, and they assume facts to be non-defeasible. We assume that all knowledge is defeasible due to the nature of medical knowledge, which is constantly expanding…
3.1, A defeasible rule is denoted 'alpha1 ^ … ^ alphaN -> alpha0' where alphai is a literal… A defeasible fact is denoted 'alpha' where alpha is a literal. A belief is either a defeasible rule of a defeasible fact.
3.2, A belief base associated with an agent x is a finite set…
3.3… A defeasible derivation of (a literal) ‘alpha’ from (a set of beliefs)… is a finite sequence alpha1, alpha2, …, alphaN of literals such that alphaN is alpha and each literal… is in the sequence because…
3.4, An argument constructed from a set of, possibly inconsistent, beliefs… is a minimally consistent set from which the claim can be defeasibly derived…
Thursday, 29 March 2007
What is an Inquiry Dialogue?
Paragraph taken from the introduction of 'A Generative Inquiry Dialogue System' by Elizabeth Black and Anthony Hunter (2007)
In this paper we focus on inquiry dialogues. Walton and Krabbe define an inquiry dialogue as arising from an initial situation of "general ignorance" and as having the main goal to achieve the "growth of knowledge and agreement". Each indiviual participating in an inquiry dialogue has the goal to "find a 'proof' or destroy one" ('Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning', page 66)... we have defined two different types of inquiry dialogue, each of which we believe fits the general definition:
- warrant inquiry dialogue - the 'proof' takes the form of a dialectical tree (essentially a tree with an argument at each node, whose arcs represent the counter-argument relation and that has at its root an argument whose claim is the topic of the dialogue).
- argument inquiry dialogue - the 'proof' takes the form of an argument for the topic of the dialogue.
Argument inquiry dialogues are commonly embedded in warrant inquiry dialogues. In this paper, we will focus only on argument inquiry dialogues.
In this paper we focus on inquiry dialogues. Walton and Krabbe define an inquiry dialogue as arising from an initial situation of "general ignorance" and as having the main goal to achieve the "growth of knowledge and agreement". Each indiviual participating in an inquiry dialogue has the goal to "find a 'proof' or destroy one" ('Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning', page 66)... we have defined two different types of inquiry dialogue, each of which we believe fits the general definition:
- warrant inquiry dialogue - the 'proof' takes the form of a dialectical tree (essentially a tree with an argument at each node, whose arcs represent the counter-argument relation and that has at its root an argument whose claim is the topic of the dialogue).
- argument inquiry dialogue - the 'proof' takes the form of an argument for the topic of the dialogue.
Argument inquiry dialogues are commonly embedded in warrant inquiry dialogues. In this paper, we will focus only on argument inquiry dialogues.
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