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- W2441109831 abstract "Learning classifier systems (LCSs) have existed for nearly twenty years (Holland & Reitman, 1978). Research efforts in reinforcement learning (RL), evolutionary computation (EC), and neural networks have enhanced the original LCS paradigm. New thoughts from these areas have created a renaissance period for the LCS. This paper highlights some key LCS advancements and the fields that inspired them. One inspiration, from neural networks, is examined for a novel LCS approach to autonomous mobile robots. A simple, LCS-controlled robot simulation is presented. This simulation shows the potential benefits of combined biological paradigms and the hybridization of ideas in the LCS. Future directions for LCS research are discussed." @default.
- W2441109831 created "2016-06-24" @default.
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- W2441109831 date "1996-01-01" @default.
- W2441109831 modified "2023-09-25" @default.
- W2441109831 title "Classifier System Renaissance: New Analogies, New Directions" @default.
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- W2441109831 doi "https://doi.org/10.7551/mitpress/3242.003.0099" @default.
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