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Challenges to Scaling-Up Agent Coordination Strategies

  • Chapter
An Application Science for Multi-Agent Systems

Part of the book series: Multiagent Systems, Artificial Societies, and Simulated Organizations ((MASA,volume 10))

Abstract

There is more to scaling up agent-based systems than simply increasing the number of agents involved. Many of the challenges to making agent-based systems work in more realistic settings arise from the characteristics of the agents’ tasks and environment, and the expectations of the systems’ users. In this chapter, my goal is thus to emphasize this broader array of challenges to coordinating agent-based systems, as a step both towards extending our understanding of scale-up issues as well as towards developing richer metrics for evaluating the degree to which coordination strategies for agent-based systems can apply to more demanding applications.

A condensed version of this chapter appeared as “Scaling-Up Agent Coordination Strategies” in IEEE Computer 34(7):39–46, July 2001.

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References

  • Andersson, A., M. Tenhunen, and F. Ygge. “Integer Programming for Combinatorial Auction Winner Determination.” Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000), pages 39–46, IEEE Computer Society Press, July 2000.

    Google Scholar 

  • Azoulay-Schwartz, R. and S. Kraus. “Assessing Usage Patterns to Improve Data Allocations via Auctions.” Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000), pages 47–55, IEEE Computer Society Press, July 2000.

    Google Scholar 

  • Bojinov, H., A. Casal, and T. Hogg. “Multiagent Control of Self-reconfigurable Robots.” Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000), pages 143–150, IEEE Computer Society Press, July 2000.

    Google Scholar 

  • Boutilier, C. “Multiagent Systems: Challenges and opportunities for decision-theoretic planning.” AI Magazine 20(4):35–43, Winter 1999.

    Google Scholar 

  • Brooks, C. H., E. H. Durfee, and A. Armstrong. “An Introduction to Congregating in Multiagent Systems.” Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000), pages 79–86, IEEE Computer Society Press, July 2000.

    Google Scholar 

  • Clement, B. J. and E. H. Durfee, 1999. “Top-Down Search for Coordinating the Hierarchical Plans of Multiple Agents.” In Proceedings of the Third Conference on Autonomous Agents, pages 252–259, May.

    Google Scholar 

  • Decker, K. S. “TÆMS: A framework for analysis and design of coordination mechanisms.” In G. O’Hare and N. Jennings, editors, Foundations of Distributed Artificial Intelligence, Chapter 16. Wiley Inter-Science, 1995.

    Google Scholar 

  • Dellarocas, C. and M. Klein. “An experimental evaluation of domain-independent fault handling services in open multi-agent systems.” Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000), pages 39–46, IEEE Computer Society Press, July 2000.

    Google Scholar 

  • Durfee, E. H. and V. R. Lesser. “Partial Global Planning: A coordination framework for distributed hypothesis formation.” IEEE Transactions on Systems, Man, and Cybernetics SMC-21(5):1167–1183, September 1991.

    Google Scholar 

  • Durfee, E. H. “Organisations, Plans, and Schedules: An Interdisciplinary Perspective on Coordinating AI Systems.” Journal of Intelligent Systems 3(2–4):157–187, 1993.

    Google Scholar 

  • Durfee, E. H. “Distributed continual planning for unmanned ground vehicle teams.” AI Magazine 20(4):55–61, Winter 1999.

    Google Scholar 

  • Ephrati, E., M. E. Pollack, and J. S. Rosenschein. “A tractable heuristic that maximizes global utility through local plan combination.” In Proceedings of the First International Conf. on Multi-Agent Systems (ICMAS-95), pages 94–101, June 1995.

    Google Scholar 

  • Estlin, T., T. Mann, A. Gray, G. Rabideau, R. Castano, S. Chien and E. Mjolsness, “An Integrated System for Multi-Rover Scientific Exploration,” Proceedings of the Sixteenth National Conference of Artificial Intelligence (AAAI-99), Orlando, FL, July 1999.

    Google Scholar 

  • Fenster, M., S. Kraus, and J. S. Rosenschein. “Coordination without communication: experimental validation of focal point techniques.” Proceedings of the First International Conf. on Multi-Agent Systems (ICMAS-95), pages 102–108, June 1995.

    Google Scholar 

  • Ferber, J. Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Harlow England, 1999.

    Google Scholar 

  • Fujishima, Y., Leyton-Brown, K., and Shoham, Y. “Taming the computational complexity of combinatorial auctions: Optimal and approximate approaches.” In Sixteenth International Joing Conference on Artificial Intelligence (IJCAI-99). 1999.

    Google Scholar 

  • Gasser, L., C. Braganza, and N. Herman. “MACE: A flexible testbed for distributed AI research.” In M. N. Huhns, editor, Distributed Artificial Intelligence, pages 119–152, Pitman Publishers, 1987.

    Google Scholar 

  • Georgeff, M. P. “Communication and Interaction in multi-agent planning.” In Proceedings of the Third National Conf. on Artificial Intelligence (AAAI-83), pages 125–129, July 1983.

    Google Scholar 

  • Gray, R. S., D. Kotz, R. A. Peterson, Jr., P. Gerken, M. Hofmann, D. Chacon, G. Hill, and N. Suri. “Mobile-Agent versus Client/Server Performance: Scalability in an Information-Retrieval Task.” Technical ReportTR2001-386, Dept. of Computer Science, Dartmouth College, January 2001.

    Google Scholar 

  • Grosz, B. J. and S. Kraus. “Collaborative Plans for Complex Group Action.” Artificial Intelligence. 86(2), pp. 269–357, 1996.

    Article  MathSciNet  Google Scholar 

  • Jennings, N. R. “Commitments and Conventions: The foundation of coordination in multi-agent systems.” The Knowledge Engineering Review, 2(3):223–250, 1993.

    Google Scholar 

  • Jennings, N. R. “An Agent-based Approach for Building Complex Software Systems.” Communications of the ACM 44(4):35–41, April 2001.

    Article  MathSciNet  Google Scholar 

  • Kinny, D., M. Ljungberg, A. S. Rao, E. Sonenberg, G. Tidhar, and E. Werner. “Planned Team Activity.” In C. Castelfrachi and E. Werner, editors, Artificial Social Systems. Springer-Verlag, Amsterdam, 1994.

    Google Scholar 

  • Kumar, S., P. R. Cohen, and H. J. Levesque. “The adaptive agent architecture: Achieving fault-tolerance using persistent broker teams.” Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000), pages 159–166, IEEE Computer Society Press, July 2000.

    Google Scholar 

  • Lansky, A. L. “Localized Search for Controlling Automated Reasoning.” In Proceedings of the DARPA Workshop on Innovative Approaches to Planning, Scheduling, and Control, pages 115–125, November 1990.

    Google Scholar 

  • Lerman, K. and O. Shehory. “Coalition Formation for Large-Scale Electronic Markets.” Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000), pages 167–174, IEEE Computer Society Press, July 2000.

    Google Scholar 

  • Lesser, V. R. and D. D. Corkill. “Functionally accurate, cooperative distributed systems.” IEEE Trans. on Systems, Man, and Cybernetics SMC-11(1):81–96, 1981.

    Google Scholar 

  • Paolucci, M., Z. Niu, K. Sycara, C. Domashnev, S. Owens and M. van Velsen “Matchmaking to Support Intelligent Agents for Portfolio Management.” In Proceedings of AAAI2000.

    Google Scholar 

  • Prietula, M. J., K. M. Carley, and L. Gasser, editors. Simulating Organizations: Computational Models of Institutions and Groups. AAAI Press/MIT Press, Menlo Park, CA, 1998.

    Google Scholar 

  • Sandholm, T. W. “Distributed Rational Decision Making.” Chapter 5 in (Weiss, 1999).

    Google Scholar 

  • Shoham, Y. and M. Tennenholtz. “On Social Laws for Artificial Agent Societies: Off-line design.” Artificial Intelligence 72(1–2):231–252, 1994.

    Google Scholar 

  • Stone, P. and M. Veloso. “Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork.” Artificial Intelligence 100(2), June 1999.

    Google Scholar 

  • Tambe, M., W. L. Johnson, R. M. Jones, F. Koss, J. E. Laird, P. S. Rosenbloom, and K. Schwamb. “.” AI Magazine, 16(1):15–39, Spring 1995.

    Google Scholar 

  • Tambe, M., and W. Zhang. “Towards flexible teamwork in persistent teams: extended report.” Journal of Autonomous Agents and Multi-agent Systems 3(2): 159–183, June 2000.

    Google Scholar 

  • Weiss, G., editor. Multiagent Systems: A modern approach to distributed artificial intelligence. The MIT Press, Cambridge MA, 1999.

    Google Scholar 

  • Wellman, M. P. “A market-oriented programming environment and its application to distributed multicommodity flow problems.” Journal of Artificial Intelligence Research, 1:1–23, 1993.

    MATH  Google Scholar 

  • Wolfram, S. A New Kind of Science. Wolfram Media Inc., 2002.

    Google Scholar 

  • Wooldridge, M. Reasoning About Rational Agents. The MIT Press, July 2000.

    Google Scholar 

  • Yokoo, M. and Hirayama, K. “Algorithms for distributed constraint satisfaction: A review.” Autonomous Agents and Multi-agent Systems, 3(2):189–211, 2000.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109

    Edmund H. Durfee

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  1. Edmund H. Durfee
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Editor information

Editors and Affiliations

  1. Honeywell Laboratories, USA

    Thomas A. Wagner

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© 2004 Springer Science + Business Media, Inc.

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Durfee, E.H. (2004). Challenges to Scaling-Up Agent Coordination Strategies. In: Wagner, T.A. (eds) An Application Science for Multi-Agent Systems. Multiagent Systems, Artificial Societies, and Simulated Organizations, vol 10. Springer, Boston, MA. https://doi.org/10.1007/1-4020-7868-4_7

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  • DOI: https://doi.org/10.1007/1-4020-7868-4_7

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4020-7867-5

  • Online ISBN: 978-1-4020-7868-2

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