Algorithmic Mechanism Design Algorithmic Mechanism Design Contact

We consider algorithmic problems in a distributed setting where the participants cannot be assumed to follow the algorithm but rather their own self-interest. As such participants, termed agents, are capable of manipulating the algorithm, the algorithm designer should ensure in advance that the agents' interests are best served by behaving correctly. Following notions from the eld of mechanism design, we suggest a framework for studying such algorithms. In this model the algorithmic solution is adorned with payments to the participants and is termed a mechanism. The payments should be carefully chosen as to motivate all participants to act as the algorithm designer wishes. We apply the standard tools of mechanism design to algorithmic problems and in particular to the shortest path problem. Our main technical contribution concerns the study of a representative problem, task scheduling , for which the standard tools do not suuce. We present several theorems regarding this problem including an approximation mechanism, lower bounds and a randomized mechanism. We also suggest and motivate extensions to the basic model and prove improved upper bounds in the extended model. Many open problems are suggested as well.

[1]  E. H. Clarke.  Multipart pricing of public goods , 1971 .

[2]  Tad Hogg,et al.  Distributed Computation as an Economic System , 1995 .

[3]  N. S. Barnett,et al.  Private communication , 1969 .

[4]  Eithan Ephrati,et al.  The Clarke Tax as a Consensus Mechanism Among Automated Agents , 1991, AAAI.

[5]  Jerry R. Green,et al.  Characterization of Satisfactory Mechanisms for the Revelation of Preferences for Public Goods , 1977 .

[6]  Yoav Shoham,et al.  A Dynamic Theory of Incentives in Multi-Agent Systems , 1997, IJCAI.

[7]  Jan Karel Lenstra,et al.  Approximation algorithms for scheduling unrelated parallel machines , 1987, 28th Annual Symposium on Foundations of Computer Science (sfcs 1987).

[8]  William Vickrey,et al.  Counterspeculation, Auctions, And Competitive Sealed Tenders , 1961 .

[9]  Journal of the Association for Computing Machinery , 1961, Nature.

[10]  Dorit S. Hochbaum,et al.  Approximation Algorithms for NP-Hard Problems , 1996 .

[11]  Donald F. Ferguson,et al.  Economic models for allocating resources in computer systems , 1996 .

[12]  Michael P. Wellman,et al.  Auction Protocols for Decentralized Scheduling , 2001, Games Econ. Behav..

[13]  Christos H. Papadimitriou,et al.  Computational aspects of organization theory , 1996 .

[14]  Nathan Linial,et al.  Game-theoretic aspects of computing , 1994 .

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

[16]  Ellis Horowitz,et al.  Exact and Approximate Algorithms for Scheduling Nonidentical Processors , 1976, JACM.

[17]  Deborah Estrin,et al.  Pricing in Computer Networks: Reshaping the Research Agenda , 2020, The Internet and Telecommunications Policy.

[18]  Michael P. Wellman,et al.  A market protocol for decentralized task allocation , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[19]  Noam Nisan,et al.  Algorithmic mechanism design (extended abstract) , 1999, STOC '99.

[20]  Leslie Lamport,et al.  The Byzantine Generals Problem , 1982, TOPL.

[21]  Ariel Orda,et al.  Architecting noncooperative networks , 1995, Eighteenth Convention of Electrical and Electronics Engineers in Israel.

[22]  S. Clearwater.  Market-based control: a paradigm for distributed resource allocation , 1996 .

[23]  Mihalis Yannakakis,et al.  On the value of information in distributed decision-making (extended abstract) , 1991, PODC '91.

[24]  Theodore Groves,et al.  Incentives in Teams , 1973 .

[25]  S HochbaDorit.  Approximation Algorithms for NP-Hard Problems , 1997 .

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

[27]  T. Sandholm.  Limitations of the Vickrey Auction in Computational Multiagent Systems , 1996 .