Strategic Considerations in Agent Dialogue games

1. Strategic Considerations in Agent Dialogue games Christos Hadjinikolis Supervisors: Dr. Sanjay Modgil, Dr. Elizabeth Black, Prof. Peter McBurney

2. Reaching Agreements • Negotiation dialogues • A bargainover the division of some resource • Negotiation is intended to aim at compromise • Deliberation dialogues • Decidethe actionor the course of actionsthat they should adopt in order to bring about some task King's College London Department of Informatics

3. Persuasion Dialogues • How do persuasion dialogues fit into negotiation and deliberation? • “A participant tries to convincethe 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 King's College London Department of Informatics

4. Persuasion Dialogues • How does this form of dialogues fit into the picture? • How can such conflicts appear in these types of dialogues? King's College London Department of Informatics

5. Example A B King's College London Department of Informatics

6. Persuasion Dialogues • Deliberation dialogues: • In order to agreeon accepting the proposed course of actions, the proposing party needs to firstconvince 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 preferencesof an agent and the offerthat it receives” H. Prakken, “A Protocol for Arguing about Rejections in Negotiation” King's College London Department of Informatics

7. Persuasion Dialogues • Employed as embedded dialogues or sub-dialogues • Resolve conflicts • Optimisethe duration of a dialogue and allow for rationalisingabout a response King's College London Department of Informatics

8. Strategising • Strategisingin 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” King's College London Department of Informatics

9. Strategising • What are the prerequisites of Strategising: • Informationabout one’s opponent • Abilities • Objectives • Its knowledge • Opponent modeling King's College London Department of Informatics

10. 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 observingother 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 King's College London Department of Informatics

11. 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 King's College London Department of Informatics

12. Opponent Modelling A Its opponent’s KB An agent’s own KB A B B C C D D King's College London Department of Informatics

13. 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 King's College London Department of Informatics

14. 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. King's College London Department of Informatics

15. The ASPIC Framework (2006) • Developed by: • Leila Amgoud • Martin Caminada • Claudette Cayrol • Marie-Christine Lagasquie-Schieux • Henry Prakken • Gerard Vreeswijk King's College London Department of Informatics

16. ASPIC • Relied on Dung’s framework and added to its expressiveness: • Described a general logical language L • Differentiated between strictand defeasiblerules • Defined argumentswith respect to their logical structure • Logical premises • Rules • Conclusion • Differentiated between the conflictsbetween arguments • Undercutting attacks • Rebutting attacks King's College London Department of Informatics

17. From ASPICto ASPIC+ • Added another form of attack : undermining • From the notion of contradictionbetween formulas φand ￢φ,to an abstract relation of contrariness between formulas • Distinguished between 4 types of premises • axioms, ordinary,assumptions,issues • Attackssucceed as defeatrelationsbased on: • preference orderings on arguments which in turn are based on: • Priority orderings over defeasible rules and premises • Unlike ASPIC, Prakken’sASPIC+ showed satisfaction of Caminada’s and Amgoud’srationality postulates when accounting preferences King's College London Department of Informatics

18. Our idea • Knowledge representation: • agent’s ’s Knowledge base • : <, , , ... , > • n: number of agents in the environment • All agents share the same logical language L andcontrary relationdefinition King's College London Department of Informatics

19. Our idea • , ,,> What believes is agent ’s : • Premises ( • Pre-ordering over premises ( • () • Pre-ordering overt) • Goals () King's College London Department of Informatics

20. Multi-Agent Knowledge Base King's College London Department of Informatics

21. The proposed approach • The information gathered about the interlocutor • Based on a set of protocol rules • Backtracking • Commitmentstores 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 King's College London Department of Informatics

22. The strategy function King's College London Department of Informatics

23. Example • Let’s assume a dialogue protocol for grounded semantics: • Backtrackingis allowed • Commitment store • Knowledgeabout what the interlocutor believes is 100% correct • Under the grounded protocol rules the proponent is not allowed to repeat the same move twice whileopponent can. King's College London Department of Informatics

24. Example: A dialogue game for grounded semantics C A F B D G E H King's College London Department of Informatics

25. Example: A dialogue game for grounded semantics C A F B D G E H King's College London Department of Informatics

26. Example: A dialogue game for grounded semantics C A F B D G E H King's College London, Department of Informatics

27. Example: A dialogue game for grounded semantics Agi’s Knowledge Base s=> a p => ¬s r=> a p => ¬a p => q ̴̴q => ¬r s p r W X Y Z T F K King's College London, Department of Informatics

28. Example: A dialogue game for grounded semantics Agi’s Knowledge Base s=> a p => ¬s r=> a p => ¬a p => q ̴̴q => ¬r s p r W X Y Z T F K King's College London, Department of Informatics

29. Example: A dialogue game for grounded semantics … ¬a ,¬a => g Agi’s Knowledge Base s=> a p => ¬s r=> a p => ¬a p => q ̴̴q => ¬r s p r W X Y Z T F win! K King's College London, Department of Informatics

30. Example: A dialogue game for grounded semantics … ¬a ,¬a => g Agi’s Knowledge Base s=> a p => ¬s r=> a p => ¬a p => q ̴̴q => ¬r s p r W F Z X T Z Y Y X T F X Y G E K G K G E K E r => a r r => a, p => q r, p ̴̴q => ¬r King's College London, Department of Informatics

31. Conclusions • If an agent’s beliefs are correctand completethen 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 King's College London Department of Informatics

32. 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 King's College London Department of Informatics

33. 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 attackin 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 King's College London Department of Informatics

34. Other characteristics of the system A B A>B g → f s → ¬ f King's College London Department of Informatics

35. Future directions • Research strategising in iterativedialogues • 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 King's College London Department of Informatics

36. Thanks King's College London Department of Informatics