Abstract
This paper explores how to design good rules for multiple learning agents in scheduling problems and investigates what kind of factors are required to find good solutions with small computational costs. Through intensive simulations of crew task scheduling in a space shuttle/station, the following experimental results have been obtained: (1) an integration of (a) a solution improvement factor, (b) an exploitation factor, and (c) an exploration factor contributes to finding good solutions with small computational costs; and (2) the condition part of rules, which includes flags indicating overlapping, constraints, and same situation conditions, supports the contribution of the above three factors.
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Paper submitted to the 2nd Pacific Rim InternationalWorkshop on Multi-Agents (PRIMA’99)
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Takadama, K., Watabe, M., Shimohara, K., Nakasuka, S. (1999). How to Design Good Rules for Multiple Learning Agents in Scheduling Problems?. In: Nakashima, H., Zhang, C. (eds) Approaches to Intelligence Agents. PRIMA 1999. Lecture Notes in Computer Science(), vol 1733. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46693-2_10
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DOI: https://doi.org/10.1007/3-540-46693-2_10
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