Adding temporary memory to ZCS
Adaptive Behavior
Triggered Rule Discovery in Classifier Systems
Proceedings of the 3rd International Conference on Genetic Algorithms
Two Views of Classifier Systems
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
Intelligent behavior as an adaptation to the task environment
Intelligent behavior as an adaptation to the task environment
Zcs: A zeroth level classifier system
Evolutionary Computation
Classifier fitness based on accuracy
Evolutionary Computation
An analysis of generalization in the xcs classifier system
Evolutionary Computation
Reward allotment in an event-driven hybrid learning classifier system for online soccer games
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Intrusion detection with evolutionary learning classifier systems
Natural Computing: an international journal
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
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Extended Classifier Systems, or XCS, have been shown to be successful at developing accurate, complete and compact mappings of a problem's payoff landscape. However, the experimental results presented in the literature frequently utilize population sizes significantly larger than the size of the search space. This resource requirement may limit the range of problem/hardware combinations to which XCS can be applied. In this paper two sets of modifications are presented that are shown to improve performance in small sizeconstrained 6-Multiplexer and Woods-2 problems.