Some Recent Results and Open Questions in Distributed Resource Allocation

When rational but myopic agents negotiate over the exchange of indivisible resources, any restriction to the negotiation protocol may prevent the system from converging to a socially optimal allocation in the general case. On the other hand, restrictions to the expressive power of the utility functions used by individual agents to represent their preferences can sometimes reduce the complexity of resource allocation problems and allow for very restricted negotiation protocols to work effectively. This paper reviews a number of recent theoretical results addressing these issues. Specifically, it analyses how the confinement to structurally simple deals and to certain restricted classes of cardinal utility functions can enable agents to move to an optimal allocation, while reducing the overall complexity of the process. The case of complex deals is also studied, and both restrictions on utility functions and specially designed protocols are proposed which drastically reduce the complexity of the resource allocation process.

[1]  Tuomas Sandholm.  Contract Types for Satisficing Task Allocation:I Theoretical Results , 2002 .

[2]  R. M. Adelson,et al.  Utility Theory for Decision Making , 1971 .

[3]  Sarit Kraus,et al.  Strategic Negotiation in Multiagent Environments , 2001, Intelligent robots and autonomous agents.

[4]  Steven J. Brams,et al.  Fair division - from cake-cutting to dispute resolution , 1998 .

[5]  Gregory E. Kersten,et al.  Are All E-Commerce Negotiations Auctions? , 2000, COOP.

[6]  A. Sen,et al.  Collective Choice and Social Welfare , 2017 .

[7]  Pattie Maes,et al.  Challenger: a multi-agent system for distributed resource allocation , 1997, AGENTS '97.

[8]  Yann Chevaleyre,et al.  Protocols for Tractable Resource Allocation with k-additive Utilities , 2005 .

[9]  H. Moulin.  Axioms of Cooperative Decision Making , 1988 .

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

[11]  Noam Nisan,et al.  Bidding and allocation in combinatorial auctions , 2000, EC '00.

[12]  Ronald M. Harstad,et al.  Computationally Manageable Combinational Auctions , 1998 .

[13]  Michael Wooldridge,et al.  The complexity of contract negotiation , 2005, Artif. Intell..

[14]  Nicolas Maudet,et al.  Resource Allocation in Egalitarian Agent Societies , 2003 .

[15]  Nicolas Maudet,et al.  On optimal outcomes of negotiations over resources , 2003, AAMAS '03.

[16]  Yann Chevaleyre,et al.  Multiagent Resource Allocation with K -additive Utility Functions , 2004 .

[17]  Yann Chevaleyre,et al.  On Maximal Classes of Utility Functions for Efficient one-to-one Negotiation , 2005, IJCAI.

[18]  Reid G. Smith,et al.  The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver , 1980, IEEE Transactions on Computers.

[19]  Michel Grabisch,et al.  K-order Additive Discrete Fuzzy Measures and Their Representation , 1997, Fuzzy Sets Syst..

[20]  Guillermo Ricardo Simari,et al.  Multiagent systems: a modern approach to distributed artificial intelligence , 2000 .

[21]  Yann Chevaleyre,et al.  Negotiating over small bundles of resources , 2005, AAMAS '05.