Abstract
The big strength of intelligent agents — their communicative abilities — can often change into a big hindrance in real-world applications of collaborative problem solving. One can often observe that communication overhead annihilates the merits of partitioning the given problem. In this article, I introduce a concept called dynamic reconfiguration that allows for adapting the multi agent system structure to the given problem structure thus saving communication costs. The main focus lies on a novel consensus protocol that supports this reconfiguration and assumes benevolent, trustworthy agents. Hence, it is like the whole reconfiguration approach itself mainly applicable for rather closed systems, e. g. information or control systems. The protocol claims to enhance the efficiency of consensus finding by using several different phases of negotiation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
P. Berlandier and B. Neveu. Problem partition and solvers coordination in distributed constraint satisfaction. In Proceedings of the Workshop on Parallel Processing in Artificial Intelligence (PPAI-95), Montréal, Canada, 1995.
S. E. Conry, R. A. Meyer, and V. R. Lesser. Multistage negotiation in distributed planning. In A. H. Bond and L. Gasser, editors, Readings in Distributed Artificial Intelligence, pages 367–384. Morgan Kaufmann Publishers, 1988.
J. de Kleer. A comparison of ATMS and CSP techniques. In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), pages 290–296, 1989.
L. Garrido-Luna and K. P. Sycara. Towards a totally distributed meeting scheduling system. In G. Görz and S. Hölldobler, editors, KI-96: Advances in Artificial Intelligence, volume 1137 of LNAI, pages 85–97. Springer, 1996.
M. Hannebauer and U. Geske. Coordinating distributed CLP-solvers in medical appointment scheduling. In Proceedings of the Twelfth International Conference on Applications of Prolog (INAP-99), pages 117–125, Tokyo, Japan, 1999.
M. Hannebauer and R. Kiihnel. Dynamic reconfiguration in collaborative problem solving. In H.-D. Burkhard, L. Czaja, H.-S. Nguyen, and P. Starke, editors, Proceedings of the Eighth Workshop on Concurrency, Specification and Programming (CS&P-99), pages 71–82, Warsaw, Poland, 1999.
M. N. Huhns and M. P. Singh, editors. Readings in Agents. Morgan Kaufmann Publishers, 1998.
N. R. Jennings and M. J. Wooldridge. Agent Technology — Foundations, Applications, and Markets. Springer, 1998.
J.-S. Liu and K. P. Sycara. Distributed meeting scheduling. In Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, Atlanta, USA, 1994.
Q. Y. Luo, P. G. Hendry, and J. T. Buchanan. Heuristic search for distributed constraint satisfaction problems. Research Report KEG-6–92, Department of Computer Science, University of Strathclyde, Glasgow Gl 1XH, UK, 1992.
K. Marriot and P. J. Stuckey. Programming with Constraints — An Introduction. MIT Press, 1998.
T. Nguyen and Y. Deville. A distributed arc-consistency algorithm. Science of Computer Programming, 30(1–2):227–250, 1998.
W. Reisig. Elements of Distributed Algorithms — Modeling and Analysis with Petri Nets. Springer, 1998.
R. G. Smith. The contract net protocol: High-level communication and control in a distributed problem solver. In A. H. Bond and L. Gasser, editors, Readings in Distributed Artificial Intelligence, pages 357–366. Morgan Kaufmann Publishers, 1988.
G. Solotorevsky, E. Gudes, and A. Meisels. Modeling and solving distributed constraint satisfaction problems (DCSPs). In Proceedings of the Conference on Constraint-Processing (CP-96), 1996.
K. P. Sycara, S. F. Roth, N. Sadeh, and M. S. Fox. Distributed constrained heuristic search. IEEE Transactions on Systems, Man, and Cybernetics, 21 (6): 1446–1461, 1991.
G. Tel. Distributed control algorithms for AI. In G. Weiss, editor, Multiagent Systems — A Modern Approach to Distributed Artificial Intelligence, pages 562–569. MIT Press, 1999.
D. Waltz. Understanding line drawing of scences with shadows. In P. Winston, editor, The Psychology of Computer Vision, pages 19–91. McGraw-Hill, 1975.
M. Yokoo, E. H. Durfee, T. Ishida, and K. Kuwabara. The distributed constraint satisfaction problem: Formalization and algorithms. IEEE Transactions on Knowledge and DATA Engineering, 10(5), 1998.
M. Yokoo and K. Hirayama. Distributed constraint satisfaction algorithm for complex local problems. In Proceedings of the Third International Conference on Multi-Agent Systems (ICMAS-98), pages 372–379, Paris, France, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Hannebauer, M. (2000). Multiphase Consensus Communication in Collaborative Problem Solving. In: Hommel, G. (eds) Communication-Based Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9608-4_11
Download citation
DOI: https://doi.org/10.1007/978-94-015-9608-4_11
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-5399-2
Online ISBN: 978-94-015-9608-4
eBook Packages: Springer Book Archive