Article

Get Real! XCS with Continuous-Valued Inputs

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Learning Classifier Systems, From Foundations to Applications

Pages 209 - 222

Published: 01 January 2000 Publication History

Abstract

Classifier systems have traditionally taken binary strings as inputs, yet in many real problems such as data inference, the inputs have real components. A modified XCS classifier system is described that learns a non-linear real-vector classification task.

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Cited By

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Yatsu NShiraishi HSato HTakadama KSilva SPaquete L(2023)Exploring High-dimensional Rules Indirectly via Latent Space Through a Dimensionality Reduction for XCSProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590439(606-614)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583131.3590439
Shiraishi HHayamizu YSato HTakadama KWagner M(2022)Can the same rule representation change its matching area?Proceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528874(431-439)Online publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1145/3512290.3528874
Shiraishi HHayamizu YSato HTakadama KWagner M(2022)Absumption based on overgenerality and condition-clustering based specialization for XCS with continuous-valued inputsProceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528841(422-430)Online publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1145/3512290.3528841
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Get Real! XCS with Continuous-Valued Inputs
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
    2. Machine learning approaches

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Learning Classifier Systems, From Foundations to Applications

January 2000

346 pages

ISBN:3540677291

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Springer-Verlag

Berlin, Heidelberg

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Published: 01 January 2000

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Yatsu NShiraishi HSato HTakadama KSilva SPaquete L(2023)Exploring High-dimensional Rules Indirectly via Latent Space Through a Dimensionality Reduction for XCSProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590439(606-614)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583131.3590439
Shiraishi HHayamizu YSato HTakadama KWagner M(2022)Can the same rule representation change its matching area?Proceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528874(431-439)Online publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1145/3512290.3528874
Shiraishi HHayamizu YSato HTakadama KWagner M(2022)Absumption based on overgenerality and condition-clustering based specialization for XCS with continuous-valued inputsProceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528841(422-430)Online publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1145/3512290.3528841
Pätzel DHähner JWagner M(2022)The Bayesian learning classifier systemProceedings of the Genetic and Evolutionary Computation Conference10.1145/3512290.3528736(413-421)Online publication date: 8-Jul-2022
https://dl.acm.org/doi/10.1145/3512290.3528736
Stein ANakata MKrawiec K(2021)Learning classifier systemsProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3449726.3461414(498-527)Online publication date: 7-Jul-2021
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Shiraishi HTadokoro MHayamizu YFukumoto YSato HTakadama KKrawiec K(2021)Misclassification detection based on conditional VAE for rule evolution in learning classifier systemProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3449726.3459508(169-170)Online publication date: 7-Jul-2021
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Kozlowski NUnold OCoello Coello C(2020)Investigating exploration techniques for ACS in discretized real-valued environmentsProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion10.1145/3377929.3398079(1765-1773)Online publication date: 8-Jul-2020
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Stein ANakata MCoello Coello C(2020)Learning classifier systemsProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion10.1145/3377929.3389860(561-589)Online publication date: 8-Jul-2020
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Rudolph STomforde SHähner J(2019)Mutual Influence-aware Runtime Learning of Self-adaptation BehaviorACM Transactions on Autonomous and Adaptive Systems10.1145/334531914:1(1-37)Online publication date: 12-Sep-2019
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Ji HChen LHsiao TAuger AStützle T(2019)Real-time detection of internet addiction using reinforcement learning systemProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3319619.3326882(1280-1288)Online publication date: 13-Jul-2019
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Be real! XCS with continuous-valued inputs

On the Effects of Absumption for XCS with Continuous-Valued Inputs

Mechanisms to Alleviate Over-Generalization in XCS for Continuous-Valued Input Spaces

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