Reusing learned functionality in XCS

Author:

Alvarez Isidro M.1,Browne Will N.1,Zhang Mengjie1

Affiliation:

1. Victoria University, Wellington, New Zealand

Publisher

ACM

Reference23 articles.

1. Extracted global structure makes local building block processing effective;Butz M. V.;XCS. IlliGAL Report,2005

2. An algorithmic description of XCS

3. Evolving optimum populations with XCS classifier systems;Iqbal M.;Soft Computing,2012

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1. Exploring High-dimensional Rules Indirectly via Latent Space Through a Dimensionality Reduction for XCS;Proceedings of the Genetic and Evolutionary Computation Conference;2023-07-12

2. Theoretical Analysis of Accuracy-Based Fitness on Learning Classifier Systems;IEEE Access;2022

3. Convergence analysis of rule-generality on the XCS classifier system;Proceedings of the Genetic and Evolutionary Computation Conference;2021-06-26

4. Relatedness measures to aid the transfer of building blocks among multiple tasks;Proceedings of the 2020 Genetic and Evolutionary Computation Conference;2020-06-25

5. Self-adaptation of XCS learning parameters based on learning theory;Proceedings of the 2020 Genetic and Evolutionary Computation Conference;2020-06-25

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