Multiagent SAT (MASSAT): Autonomous Pattern Search in Constrained Domains
IDEAL '02 Proceedings of the Third International Conference on Intelligent Data Engineering and Automated Learning
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Topological analysis of AOCD-based agent networks and experimental results
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AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
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In this paper, we examine two multi-agent based representations of SATs and further experimentally study the topologies of resulting agent networks. We show that different representations will make agent networks manifest different topologies. In one presentation, the resulting agent network show obviously small-world topologies. Generally speaking, a small-world topology will computationally harden a search process. Therefore, we propose a guiding design principle that to solve a search problem by a multi-agent system, it should avoid having small-worlds among agents and it should maintain balanced intra- and inter-agent computational complexity.