Extending Answer Sets for Logic Programming Agents

We present systems of logic programming agents (LPAS) to model the interactions between decision-makers while evolving to a conclusion. Such a system consists of a number of agents connected by means of unidirectional communication channels. Agents communicate with each other by passing answer sets obtained by updating the information received from connected agents with their own private information. We introduce a credulous answer set semantics for logic programming agents. As an application, we show how extensive games with perfect information can be conveniently represented as logic programming agent systems, where each agent embodies the reasoning of a game player, such that the equilibria of the game correspond with the semantics agreed upon by the agents in the LPAS.

[1]  Gerald Pfeifer,et al.  The KR System dlv: Progress Report, Comparisons and Benchmarks , 1998, KR.

[2]  Sverrir Olafsson,et al.  Resource Allocation as an Evolving Strategy , 1996, Evolutionary Computation.

[3]  Wolfgang Faber,et al.  Disjunctive Logic Programs with Inheritance , 1999, ICLP.

[4]  A. Rubinstein,et al.  A Course in Game Theory , 1995 .

[5]  Francesco Buccafurri,et al.  Disjunctive Ordered Logic: Semantics and Expressiveness , 1998, KR.

[6]  Marina De Vos,et al.  Choice Logic Programs and Nash Equilibria in Strategic Games , 1999, CSL.

[7]  Dirk Vermeir,et al.  A Universal Fixpoint Semantics for Ordered Logic , 2000, Comput. Artif. Intell..

[8]  Hector J. Levesque,et al.  Proceedings of the 2nd International Conference on Principles of Knowledge Representation and Reasoning , 1991 .

[9]  Marina De Vos,et al.  On the Role of Negation in Choice Logic Programs , 1999, LPNMR.

[10]  Hans Tompits,et al.  On properties of update sequences based on causal rejection , 2001, Theory and Practice of Logic Programming.

[11]  José Júlio Alferes,et al.  Dynamic Logic Programming , 1998, APPIA-GULP-PRODE.

[12]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[13]  Marina De Vos,et al.  Dynamic Decision-Making in Logic Programming and Game Theory , 2002, Australian Joint Conference on Artificial Intelligence.

[14]  Gerhard Brewka.  Well-Founded Semantics for Extended Logic Programs with Dynamic Preferences , 1996, J. Artif. Intell. Res..

[15]  Jeffrey S. Rosenschein and Gilad Zlotkin.  Rules of Encounter , 1994 .

[16]  Marina De Vos,et al.  A Logic for Modeling Decision Making with Dynamic Preferences , 2000, JELIA.

[17]  J. Neumann,et al.  Theory of games and economic behavior , 1945, 100 Years of Math Milestones.

[18]  Vladimir Lifschitz,et al.  Answer set programming and plan generation , 2002, Artif. Intell..

[19]  Jeffrey S. Rosenschein,et al.  Rules of Encounter - Designing Conventions for Automated Negotiation among Computers , 1994 .

[20]  José Júlio Alferes,et al.  Updates plus Preferences , 2000, JELIA.

[21]  C.-H. Luke Ong,et al.  Full Abstraction in the Lazy Lambda Calculus , 1993, Inf. Comput..

[22]  Marina De Vos,et al.  Logic Programming Agents and Game Theory , 2001, Answer Set Programming.

[23]  Hans Tompits,et al.  Logic Programs with Compiled Preferences , 2000, ECAI.

[24]  Chiaki Sakama,et al.  Representing Priorities in Logic Programs , 1996, JICSLP.

[25]  José Júlio Alferes,et al.  Logics in Artificial Intelligence: European Workshop, JELIA '96, Evora, Portugal, September 30 - October 3, 1996, Proceedings , 1996 .

[26]  David Poole,et al.  The Independent Choice Logic for Modelling Multiple Agents Under Uncertainty , 1997, Artif. Intell..

[27]  Ilkka Niemelä,et al.  Smodels - An Implementation of the Stable Model and Well-Founded Semantics for Normal LP , 1997, LPNMR.

[28]  Dov M. Gabbay,et al.  Credulous vs. Sceptical Semantics for Ordered Logic Programs , 1991, KR.