We present a variant of the Q-learning algorithm with automatic control of the exploration rate by a competition scheme. The theoretical approach is accompanied by systematic simulations of a chaos control
task. Finally, we give interpretations of the algorithm in the context of computational ecology and neural networks.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:32411 |
Date | 10 December 2018 |
Creators | Der, Ralf, Herrmann, Michael |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
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