Rule-Based Evolutionary Online Learning Systems: A Principled Approach to LCS Analysis and Design
作者： Martin V. Butz
DOI:
关键词: Classifier (UML) 、 Artificial intelligence 、 Machine learning 、 Cognitive learning 、 Computer science 、 Rule-based system 、 Binary classification 、 Reinforcement learning 、 Online learning 、 Computational complexity theory
摘要: Prerequisites.- Simple Learning Classifier Systems.- The XCS System.- How Works: Ensuring Effective Evolutionary Pressures.- When Towards Computational Complexity.- Search: Building Block Processing.- in Binary Classification Problems.- Multi-Valued Reinforcement Facetwise LCS Design.- Cognitive Summary and Conclusions.
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