Accepted:
December 2004
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/vol11/ikeda01/ | © Copyright 2005 | |||
| Volume 11 | Received: Accepted: |
November 2004 December 2004 |
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Genetic policy search using exemplar based representations
Kokolo Ikeda |
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| Abstract | |
| Direct policy search (DPS) is a method for machine learning, where the policy is represented by some parameters and they are optimized by evaluating the policy directly. We introduce exemplar based policy (EBP) optimization as a framework of DPS. An EBP is a policy composed of a set of exemplars which is parameter to be optimised, and a case-based action selector. An actual implementation with GA optimiser, genetic policy search, is introduced and its performances in two problem domains are shown. | |
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Multimedia Links (none) Reference Links (none) Citation Reference Kokolo Ikeda 2005, Genetic policy search using exemplar based representations, Complexity International, Volume 11, Paper ID: ikeda01, URL: http://www.complexity.org.au/vol11/ikeda01/ |
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