Modularity and Communication in Multiagent Planning
نویسندگان
چکیده
Automation of planning techniques can potentially save a great deal of design and programming time, and can help robots design plans when human help is not available. Currently, the computational cost of machine planning algorithms prevents wide-spread use of these systems, and these costs are magni ed in multiagent systems. The most expensive and time-consuming aspect of multiagent systems, communication, must be reduced if multiagent planning is to be practical. We propose a method by which agents may reduce both planning and communication costs by planning with stringent social laws, relaxing the laws as needed to nd a solution. We provide and implement a practical model for representing and relaxing social laws, and show a method for learning laws in minimal time; we also present a method for generating and relaxing exclusive resource allocations in speci c planning situations, and show that the method performs signi cantly better than random or no allocation in the average case.
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