Argumentation as distributed constraint satisfaction: applications and results

Conflict resolution is a critical problem in distributed and collaborative multi-agent systems. Negotiation via argumentation (NVA), where agents provide explicit arguments or justifications for their proposals for resolving conflicts, is an effective approach to resolve conflicts. Indeed, we are applying argumentation in some real-world multi-agent applications. However, a key problem in such applications is that a well-understood computational model of argumentation is currently missing, making it difficult to investigate convergence and scalability of argumentation techniques, and to understand and characterize different collaborative NVA strategies in a principled manner. To alleviate these difficulties, we present distributed constraint satisfaction problem (DCSP) as a computational model for investigating NVA. We model argumentation as constraint propagation in DCSP. This model enables us to study convergence properties of argumentation, and formulate and experimentally compare 16 different NVA strategies with different levels of agent cooperativeness towards others. One surprising result from our experiments is that maximizing cooperativeness is not necessarily the best strategy even in a completely cooperative environment. The paper illustrates the usefulness of these results in applying NVA to multi-agent systems, as well as to DCSP systems in general.

[1]  Steven Minton,et al.  Solving Large-Scale Constraint-Satisfaction and Scheduling Problems Using a Heuristic Repair Method , 1990, AAAI.

[2]  Makoto Yokoo,et al.  The Distributed Constraint Satisfaction Problem: Formalization and Algorithms , 1998, IEEE Trans. Knowl. Data Eng..

[3]  Hajime Sawamura,et al.  Computational dialectics for argument-based agent systems , 2000, Proceedings Fourth International Conference on MultiAgent Systems.

[4]  Milind Tambe,et al.  Towards Flexible Teamwork , 1997, J. Artif. Intell. Res..

[5]  Victor R. Lesser,et al.  Poaching and distraction in asynchronous agent activities , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[6]  Sarvapali D. Ramchurn,et al.  Argumentation-based negotiation , 2003, The Knowledge Engineering Review.

[7]  Edmund H. Durfee,et al.  Dynamic Prioritization of Complex Agents in Distributed Constraint Satisfaction Problems , 1997, AAAI/IAAI.

[8]  Sarit Kraus,et al.  Reaching Agreements Through Argumentation: A Logical Model and Implementation , 1998, Artif. Intell..

[9]  Milind Tambe,et al.  The Benefits of Arguing in a Team , 1999, AI Mag..

[10]  Vipin Kumar,et al.  Algorithms for Constraint-Satisfaction Problems: A Survey , 1992, AI Mag..

[11]  Nicholas R. Jennings,et al.  Determining successful negotiation strategies: an evolutionary approach , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[12]  Makoto Yokoo,et al.  Distributed constraint satisfaction algorithm for complex local problems , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[13]  KumarVipin Algorithms for constraint-satisfaction problems , 1992 .

[14]  Rina Dechter,et al.  Look-Ahead Value Ordering for Constraint Satisfaction Problems , 1995, IJCAI.

[15]  Katia Sycara,et al.  Multiagent coordination in tightly coupled task scheduling , 1997 .