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General Terms Algorithms, Languages

By Drew Mellor

Abstract

Motivated by the intention to increase the expressive power of learning classifier systems, we developed a new Xcs derivative, Fox-cs, where the classifier and observation languages are a subset of first order logic. We found that Fox-cs was viable at tasks in two relational task domains, poker and blocks world, which cannot be represented easily using traditional bit-string classifiers and inputs. We also found that for these tasks, the level of generality obtained by Fox-cs in the portion of population that produces optimal behaviour is consistent with Wilson’s generality hypothesis. Categories and Subject Descriptor

Topics: Xcs, blocks world, poker
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.329.9711
Provided by: CiteSeerX
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