strategic considerations in agent dialogue games

Strategic Considerations in Agent Dialogue games

Christos HadjinikolisSupervisors: Dr. Sanjay Modgil, Dr. Elizabeth Black, Prof. Peter McBurney

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Reaching Agreements

• Negotiation dialogues– A bargain over the division of some resource– Negotiation is intended to aim at compromise

• Deliberation dialogues– Decide the action or the course of actions that

they should adopt in order to bring about some task

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Persuasion Dialogues

• How do persuasion dialogues fit into negotiation and deliberation?– “A participant tries to convince the other to accept

a proposition that the last does not currently endorse”

– Persuasion dialogues are essentially the means through which we resolve conflicts of opinion

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Persuasion Dialogues

• How does this form of dialogues fit into the picture?

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• How can such conflicts appear in these types of dialogues?

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Example

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A

B

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Persuasion Dialogues

• Deliberation dialogues:– In order to agree on accepting the proposed course

of actions, the proposing party needs to first convince its interlocutor on the acceptability of the claims about beliefs on which the proposition relies

• Negotiation dialogues:– “In a negotiation dialogue it is the reject move that

shows that there is a conflict between the preferences of an agent and the offer that it receives” H. Prakken, “A Protocol for Arguing about Rejections in Negotiation”

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Persuasion Dialogues

• Employed as embedded dialogues or sub-dialogues– Resolve conflicts– Optimise the duration of a dialogue and allow for

rationalising about a response

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Strategising

• Strategising in dialogues:– The participants have self interested objectives– Dialogues do not have objectives!• As McBurney & Parsons explain in their work on “Games

That Agents Play”: “it makes no sense to talk about the goals of a dialogue since the ones who actually have goals are the participants”

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Strategising

• What are the prerequisites of Strategising:– Information about one’s opponent• Abilities• Objectives• Its knowledge

– Opponent modeling

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Opponent Modelling

• How can such a model be built?– Through collecting information during the course of a

dialogue game or through a series of dialogue games– Provided by a an external source– Through observing other dialogue games as a third

party agent– Goals: Through observing its actions in the

environment, or even during the course of dialogue games in general, either as a participant or as an observer

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Opponent Modelling

• How can such a model be represented?– Our work relies on the employment of

argumentative systems for dialogue– An opponent model can be expressed in the same

that an agent’s own beliefs are, through an argumentation framework

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Opponent Modelling

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An agent’s own KB Its opponent’s KB A

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D

A

B

C

D

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Opponent Modelling

• We rely on the employment of an argumentative system for dialogue, but based on modelling actual knowledge!

• Why?– Because we believe that otherwise it is difficult to account

for the dynamic nature of dialogues which can only be captured though the underlying logic

– This concerns the possibility of new arguments being instantiated in the course of a game

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Opponent Modelling

• For this reason we rely on ASPIC+– Why?• It explicitly models the logical content and structure of

arguments, while at the same time it accommodates many existing logics for argumentation.

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The ASPIC Framework (2006)

• Developed by:– Leila Amgoud– Martin Caminada – Claudette Cayrol– Marie-Christine Lagasquie-Schieux– Henry Prakken– Gerard Vreeswijk

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ASPIC

• Relied on Dung’s framework and added to its expressiveness:• Described a general logical language L• Differentiated between strict and defeasible rules• Defined arguments with respect to their logical structure

– Logical premises– Rules– Conclusion

• Differentiated between the conflicts between arguments– Undercutting attacks– Rebutting attacks

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From ASPIC to ASPIC+

• Added another form of attack : undermining• From the notion of contradiction between formulas φ and ￢ φ, to an abstract relation of contrariness between formulas

• Distinguished between 4 types of premises– axioms, ordinary, assumptions, issues

• Attacks succeed as defeat relations based on:– preference orderings on arguments which in turn are based on:

» Priority orderings over defeasible rules and premises

• Unlike ASPIC, Prakken’s ASPIC+ showed satisfaction of Caminada’s and Amgoud’s rationality postulates when accounting preferences

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Our idea

• Knowledge representation:– agent’s ’s Knowledge base– : <, , , ... , >

» n: number of agents in the environment

• All agents share the same logical language L and contrary relation definition

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Our idea

• , ,, >

What believes is agent ’s :– Premises (– Pre-ordering over premises (– ()– Pre-ordering over t)– Goals ()

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Multi-Agent Knowledge Base

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The proposed approach

• The information gathered about the interlocutor• Based on a set of protocol rules

– Backtracking– Commitment stores

A strategy function is employed in order to choose from a set of legal arguments, the most suiting one with respect to one’s objectives

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The strategy function

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Example

• Let’s assume a dialogue protocol for grounded semantics:– Backtracking is allowed – Commitment store– Knowledge about what the interlocutor believes is 100% correct– Under the grounded protocol rules the proponent is not allowed to

repeat the same move twice while opponent can.

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Example: A dialogue game for grounded semantics

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A

B

C

D

E

F

G

H

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Example: A dialogue game for grounded semantics

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A

B

C

D

E

F

G

H

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A

B

C

D

E

F

G

H

Example: A dialogue game for grounded semantics

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Agi’s Knowledge Base

s=> a p => ¬sr => a p => ¬ap => q q => ¬r ��s p r

X

Y

Z K

Example: A dialogue game for grounded semantics

S𝒊 𝒊 S𝒊 𝒋

T

W

F

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Agi’s Knowledge Base

s=> a p => ¬sr => a p => ¬ap => q q => ¬r ��s p r

X

Y

Z K

Example: A dialogue game for grounded semantics

S𝒊 𝒊 S𝒊 𝒋

T

W

F

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Agi’s Knowledge Base

s=> a p => ¬sr => a p => ¬ap => q q => ¬r ��s p r

X

Y

Z K

Example: A dialogue game for grounded semantics

S𝒊 𝒊 S𝒊 𝒋

T

W

F

win!

¬a ,¬a => g

…

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Agi’s Knowledge Base

s=> a p => ¬sr => a p => ¬ap => q q => ¬r ��s p r

X

Y

Z K

Example: A dialogue game for grounded semantics

S𝒊 𝒊 S𝒊 𝒋

T

W

F

¬a ,¬a => g

Y

K

Y

Z K

r => ar

��q => ¬rr => a, p => qr, p

G

E

GX

T

G

F

X

EE

…

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Conclusions

• If an agent’s beliefs are correct and complete then the game will evolve exactly as illustrated in the simulation

• The outcome of the game was affected from the instantiation of a new argument

• The strategic consideration here is for the proponent to avoid introducing arguments that could lead to the instantiation of new arguments which in turn might lead to an undesirable outcome

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Conclusions

• Though the soundness and fairness of dialogue systems that rely on abstract AFs can be shown for the purely abstract approach, we argue that such an approach is inadequate, as it fails to accommodate the fact that new arguments can be made available during the course of a dialogue

• The soundness of such systems is compromised

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Other characteristics of the system

• The opposing participants may also employ their different preference orderings on arguments, rules, or premises as those are described by ASPIC+

• The notion of attack in its three different forms is employed in the proposed system rather than that of defeat, thus we are treating preferences as moves in the dialogue

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Other characteristics of the system

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A

B

A>B

g → f

s → ¬ f

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Future directions

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• Research strategising in iterative dialogues• Develop methodologies for building an opponent model

– Account for the possibility where a participant may be in error in its modeling, or;

– May hold beliefs about its opponent’s knowledge with varying degrees of certainty

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Thanks