An AIS-Based Mathematical Programming Method
This paper developed an integrated algorithm for the general multi-agent coordination problem in a networked system that is featured by (1) no top-level coordinator; (2) subsystems operate as cooperative units. Through the mapping of such a networked system with human immune system which maintains a set of immune effectors with optimal concentration in the human body through a network of stimulatory and suppressive interactions, we designed a cooperative interaction scheme for a set of intelligent solvers, solving those sub-problems resulted from relaxing complicated constraints in a general multi-agent coordination problem. Performance was investigated by solving a resource allocation problem in distributed sensor networks.
KeywordsNetworked system Lagrangian Relaxation Artificial Immune Systems Stimulatory and Suppressive Interactions
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- 2.Cutello, V., Nicosia, G., Pavia, E.: A Parallel Immune Algorithm for Global Optimization. Computing 5, 467–475 (2006)Google Scholar
- 4.Endoh, S., Toma, N., Yamada, K.: Immune algorithm for n-TSP. In: Proceedings of 1998 IEEE International Conference on Systems, Man, and Cybernetics (1998)Google Scholar
- 5.Toma, N., Endo, S., Yamanda, K.: Immune algorithm with immune network and MHC for adaptive problem solving. In: Proceedings of 1999 IEEE International Conference on Systems, Man, and Cybernetics (1999)Google Scholar
- 9.Mailler, R., Lesser, V., Horling, B.: Cooperative negotiation for soft real-time distributed resource allocation. In: Proceedings of the Second International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 576–583 (2003)Google Scholar
- 10.Modi, P., Shen, W., Tambe, M., Yokoo, M.: An asynchronous complete method for distributed constraint optimization. In: Proceedings of Autonomous Agents and Multi-Agent Systems (2003)Google Scholar
- 11.Ostwald, J., Lesser, V., Abdallah, S.: Combinatorial auctions for resource allocation in a distributed sensor network. In: Proceedings of the 26th IEEE International Real-Time Systems Symposium, pp. 266–274 (2005)Google Scholar