Abstract
Task (re)allocation is a key problem in multiagent systems. Several different contract types have been introduced to be used for task reallocation: original, cluster, swap, and multiagent contracts. Instead of only using one of these contract types, they can be interleaved in a sequence of contract types. This is a powerful way of constructing algorithms that find the best solution reachable in a bounded amount of time. The experiments in this paper study how to best sequence the different contract types.
We show that the number of contracts performed using any one contract type does not necessarily decrease over time as one might expect. The reason is that contracts often play the role of enabling further contracts. The results also show that it is clearly profitable for the agents to mix contract types in the sequence. Sequences of different contract types reach a solution significantly closer to the global optimum and in a shorter amount of time than sequences with only one contract type. However, the best sequences consist only of two interleaved contract types: original and cluster contracts. This allows us to provide a clear prescription about protocols for anytime task reallocation.
Supported by NSF CAREER award IRI-9703122 and NSF grant IRI-9610122.
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M. R. Andersson. Performance of leveled commitment protocols for automated negotiation: An empirical study. Master’s thesis, Royal Institute of Technology, Stockholm, Sweden, 1998.
M. R. Andersson and T. W. Sandholm. Contract types for optimal task allocation: II experimental results. Technical Report WUCS-97-36, Washington University, Department of Computer Science, 1997.
M. R. Andersson and T. W. Sandholm. Leveled commitment contracting among myopic individually rational agents. Technical Report WUCS-97-47, Washington University, Department of Computer Science, 1997.
M. R. Andersson and T. W. Sandholm. Contract types for satisficing task allocation: II experimental results. In AAAI Spring Symposium Series: Satisficing Models, pages 1–7, Stanford University, CA, Mar. 1998.
M. R. Andersson and T. W. Sandholm. Leveled commitment contracting among myopic individually rational agents. In Proceedings of the Third International Conference on Multi-Agent Systems (ICMAS), pages 26–33, Paris, France, July 1998.
P. R. Cohen. Empirical Methods for Artificial Intelligence. MIT Press, 1995.
T. H. Cormen, C. E. Leiserson, and R. L. Rivest. Introduction to Algorithms. MIT Press, 1990.
R. Kalakota and A. B. Whinston. Frontiers of Electronic Commerce. Addison-Wesley Publishing Company, Inc, 1996.
R. E. Korf. Depth-first iterative-deepening: An optimal admissible tree search. Artificial Intelligence, 27(1):97–109, 1985.
R. P. McAfee and J. McMillan. Analyzing the airwaves auction. Journal of Economic Perspectives, 10(1):159–175, 1996.
H. Raiffa. The Art and Science of Negotiation. Harvard Univ. Press, Cambridge, Mass., 1982.
J. S. Rosenschein and G. Zlotkin. Rules of Encounter: Designing Conventions for Automated Negotiation among Computers. MIT Press, 1994.
T. W. Sandholm. An implementation of the contract net protocol based on marginal cost calculations. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 256–262, Washington, D.C., July 1993.
T. W. Sandholm. Limitations of the Vickrey auction in computational multiagent systems. In Proceedings of the Second International Conference on Multi-Agent Systems (ICMAS), pages 299–306, Keihanna Plaza, Kyoto, Japan, Dec. 1996.
T. W. Sandholm. Negotiation among Self-Interested Computationally Limited Agents. PhD thesis, University of Massachusetts, Amherst, 1996. Available at http://www.cs.wustl.edu/~sandholm/dissertation.ps.
T. W. Sandholm. Contract types for satis_cing task allocation: I theoretical results. In AAAI Spring Symposium Series: Satisficing Models, pages 68–75, Stanford University, CA, Mar. 1998.
T. W. Sandholm and V. R. Lesser. Advantages of a leveled commitment contracting protocol. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 126–133, Portland, OR, Aug. 1996. Extended version: University of Massachusetts at Amherst, Computer Science Department technical report 95-72.
T. W. Sandholm and F. Ygge. On the gains and losses of speculation in equilibrium markets. In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI), pages 632–638, Nagoya, Japan, Aug. 1997.
A. Sathi and M. Fox. Constraint-directed negotiation of resource reallocations. In M. N. Huhns and L. Gasser, editors, Distributed Artificial Intelligence, volume 2 of Research Notes in Artificial Intelligence, chapter 8, pages 163–193. Pitman, 1989.
S. Sen. Tradeoffs in Contract-Based Distributed Scheduling. PhD thesis, Univ. of Michigan, 1993.
R. G. Smith. The contract net protocol: High-level communication and control in a distributed problem solver. IEEE Transactions on Computers, C-29(12):1104–1113, Dec. 1980.
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Andersson, M.R., Sandholm, T.W. (1999). Sequencing of Contract Types for Anytime Task Reallocation. In: Noriega, P., Sierra, C. (eds) Agent Mediated Electronic Commerce. AMET 1998. Lecture Notes in Computer Science(), vol 1571. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48835-9_4
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