Information Fusion and Decision Making for Utility-based Agents

We describe a model of utility-based agents that synthesizes information and determines the best way to make decisions in multi-agent systems. In this model, the beliefs are decomposed into two levels. The higher level represents the possible information about the possible worlds. The lower level subsequently estimates a number function for the belief. We also present a decision theory for this kind of beliefs. The Dempster-Shafer theory is used to describe the beliefs in this decision theory. To describe utilities, we introduce a multi-set valued mapping to represent the relationship between action utilities and state partial ignorance .

[1]  Chengqi Zhang.  Cooperation Under Uncertainty in Distributed Expert Systems , 1992, Artif. Intell..

[2]  Ronen I. Brafman,et al.  On the Foundations of Qualitative Decision Theory , 1996, AAAI/IAAI, Vol. 2.

[3]  Jeffrey S. Rosenschein,et al.  Deals Among Rational Agents , 1985, IJCAI.

[4]  Yuefeng Li,et al.  A Method for Combining Interval Structures , 1998 .

[5]  Edmund H. Durfee,et al.  Negotiating Task Decomposition and Allocation Using Partial Global Planning , 1989, Distributed Artificial Intelligence.

[6]  Daniel D. Corkill,et al.  Hierarchical Planning in a Distributed Environment , 1979, IJCAI.

[7]  R. N. Pelavin.  A formal approach to planning with concurrent actions and external events , 1988 .

[8]  Chengqi Zhang,et al.  Analysis and Methodologies of Synthesis of Solutions in Distributed Expert Systems , 1996 .

[9]  Ronald Fagin,et al.  Two Views of Belief: Belief as Generalized Probability and Belief as Evidence , 1992, Artif. Intell..

[10]  Rudolf Kruse,et al.  Uncertainty and Vagueness in Knowledge Based Systems , 1991, Artificial Intelligence.

[11]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[12]  David M. Kreps.  Notes On The Theory Of Choice , 1988 .

[13]  Craig Boutilier,et al.  Toward a Logic for Qualitative Decision Theory , 1994, KR.

[14]  Ronald Fagin,et al.  Reasoning about knowledge , 1995 .

[15]  Yoav Shoham.  Agent-Oriented Programming , 1993, Artif. Intell..

[16]  Katia P. Sycara,et al.  Argumentation: Planning Other Agents' Plans , 1989, IJCAI.

[17]  Victor Lesser,et al.  Multistage negotiation in distributed planning , 1988 .

[18]  John McCarthy,et al.  Ascribing Mental Qualities to Machines , 1979 .

[19]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[20]  Sarit Kraus,et al.  Negotiation in a non-cooperative environment , 1991, J. Exp. Theor. Artif. Intell..

[21]  Didier Dubois,et al.  Possibility Theory as a Basis for Qualitative Decision Theory , 1995, IJCAI.

[22]  Jeffrey S. Rosenschein,et al.  Synchronization of Multi-Agent Plans , 1982, AAAI.

[23]  Judea Pearl,et al.  Qualitative Decision Theory , 1994, AAAI.

[24]  Edmund H. Durfee,et al.  Coordination of distributed problem solvers , 1988 .

[25]  Philippe Smets,et al.  The Transferable Belief Model , 1991, Artif. Intell..

[26]  Sarit Kraus,et al.  Collaborative Plans for Group Activities , 1993, IJCAI.

[27]  Daniel D. Corkill,et al.  THE DISTRIBUTED VEHICLE MONITORING TESTBED , 1983 .

[28]  Moisés Goldszmidt,et al.  On the Relation between Kappa Calculus and Probabilistic Reasoning , 1994, UAI.

[29]  Ronen I. Brafman,et al.  Modeling Agents as Qualitative Decision Makers , 1997, Artif. Intell..

[30]  Dayou Liu,et al.  Conflict-resolution in multi-ES cooperation system , 2008, Journal of Computer Science and Technology.

[31]  Ramesh C. Jain,et al.  Uncertainty Management in a Distributed Knowledge Based System , 1985, IJCAI.

[32]  Matthew J. Katz,et al.  Verifying plans for multiple agents , 1993, J. Exp. Theor. Artif. Intell..

[33]  Eithan Ephrati,et al.  Deriving Consensus in Multiagent Systems , 1996, Artif. Intell..

[34]  Philip R. Cohen,et al.  Plans for Discourse , 2003 .