Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic programming: an introduction: on the automatic evolution of computer programs and its applications
Layered Learning in Genetic Programming for a Cooperative Robot Soccer Problem
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
An abstraction agorithm for genetics-based reinforcement learning
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Classifier fitness based on accuracy
Evolutionary Computation
Learning Classifier Systems: Looking Back and Glimpsing Ahead
Learning Classifier Systems
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
A first assessment of the use of extended relational alphabets in accuracy classifier systems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Extracting and using building blocks of knowledge in learning classifier systems
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Utilising the expressive power of S-Expressions in Learning Classifier Systems often prohibitively increases the search space due to increased flexibility over the ternary alphabet. Selection of appropriate S-Expressions functions through domain knowledge improves scaling, as expected. Considering the Cognitive Systems roots, abstraction was included in LCS - episodic learning generalises prior to abstraction for semantic learning. This novel method is shown to provide compact results (135-MUX) and exhibits potential for scaling well (1034-MUX).