Abstract
Distributed Constraint Satisfaction Problems (DCSP) is a general framework for multi-agent coordination and conflict resolution. In most DCSP algorithms, inter-agent communication is restricted to only exchanging values of variables, since any additional information-exchange is assumed to lead to significant communication overheads and to a breach of privacy. This paper provides a detailed experimental investigation of the impact of inter-agent exchange of additional legal values among agents, within a collaborative setting. We provide a new run-time model that takes into account the overhead of the additional communication in various computing and networking environments. Our investigation of more than 300 problem settings with the new run-time model (i) shows that DCSP strategies with additional information-exchange can lead to big speedups in a significant range of settings; and (ii) provides categorization of problem settings with big speedups by the DCSP strategies based on extra communication, enabling us to selectively apply the strategies to a given domain. This paper not only provides a useful method for performance measurement to the DCSP community, but also shows the utility of additional communication in DCSP.
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References
Lesser, V., Ortiz, C., Tambe, M. (eds.): Distributed Sensor Networks: a Multiagent Perspective. Kluwer Academic Publishers, Dordrecht (2003)
Yokoo, M.: Distributed Constraint Satisfaction: Foundations of Cooperation in Multi-Agent Systems. Springer, Heidelberg (2000)
Hamadi, Y., Bessière, C., Quinqueton, J.: Backtracking in distributed constraint networks. In: Proceedings of European Conference on Artificial Intelligence (1998)
Modi, P., Jung, H., Tambe, M., Shen, W., Kulkarni, S.: A dynamic distributed constraint satisfaction approach to resource allocation. In: Proceedings of International Conference on Principles and Practice of Constraint Programming (2001)
Silaghi, M., Sam-Haroud, D., Faltings, B.: Consistency maintenance for abt. In: Proceedings of International Conference on Principles and Practice of Constraint Programming (2001)
Jung, H., Tambe, M.: Performance models for large scale multiagent systems: Using pomdp building blocks. In: Proceedings of International Joint Conference on Autonomous Agents and Multi-Agent Systems (2003)
Monfroy, E., Rety, J.H.: Chaotic iteration for distributed constraint propagation. In: ACM Symposium on Applied Computing (1999)
Haralick, R.M., Elliot, G.L.: Increasing tree search efficiency for constraint satisfaction problems. Artificial Intelligence 14, 263–313 (1980)
Armstrong, A., Durfee, E.: Dynamic prioritization of complex agents in distributed constraint satisfaction problems. In: Proceedings of International Joint Conference on Artificial Intelligence (1997)
Mailler, R., Lesser, V.: Solving distributed constraint optimization problems using cooperative mediation. In: Proceedings of International Joint Conference on Autonomous Agents and Multi-Agent Systems (2004)
Fernandez, C., Bejar, R., Krishnamachari, B., Gomes, C., Selman, B.: Communication and computation in distributed csp algorithms. In: Lesser, V., Ortiz, C., Tambe, M. (eds.) Distributed Sensor Networks. Kluwer Academic Publishers, Dordrecht (2003)
Davin, J., Modi, P.: Impact of problem centralization in distributed constraint optimization algorithms. In: Proceedings of International Joint Conference on Autonomous Agents and Multi-Agent Systems (2005)
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Jung, H., Tambe, M. (2005). On Communication in Solving Distributed Constraint Satisfaction Problems. In: Pěchouček, M., Petta, P., Varga, L.Z. (eds) Multi-Agent Systems and Applications IV. CEEMAS 2005. Lecture Notes in Computer Science(), vol 3690. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559221_42
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DOI: https://doi.org/10.1007/11559221_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29046-9
Online ISBN: 978-3-540-31731-9
eBook Packages: Computer ScienceComputer Science (R0)