Proceedings of the third international conference on Genetic algorithms
Proceedings of the third international conference on Genetic algorithms
Representational difficulties with classifier systems
Proceedings of the third international conference on Genetic algorithms
VCS: variable classifier systems
Proceedings of the third international conference on Genetic algorithms
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Top-down induction of first-order logical decision trees
Artificial Intelligence
Truth from trash: how learning makes sense
Truth from trash: how learning makes sense
Artificial Intelligence
Relational reinforcement learning
Machine Learning - Special issue on inducive logic programming
Scaling Up Inductive Logic Programming by Learning from Interpretations
Data Mining and Knowledge Discovery
Learning Logical Definitions from Relations
Machine Learning
Learning Classifier Systems, From Foundations to Applications
Learning Classifier Systems, From Foundations to Applications
Accuracy-based Neuro And Neuro-fuzzy Classifier Systems
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Classifier fitness based on accuracy
Evolutionary Computation
Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
Policy transfer with a relational learning classifier system
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Classifier systems that compute action mappings
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A Learning Classifier System Approach to Relational Reinforcement Learning
Learning Classifier Systems
Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
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
Dynamical genetic programming in xcsf
Evolutionary Computation
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Motivated by the intention to increase the expressive power of learning classifier systems, we developed a new Xcs derivative, Fox-cs, where the classifier and observation languages are a subset of first order logic. We found that Fox-cs was viable at tasks in two relational task domains, poker and blocks world, which cannot be represented easily using traditional bit-string classifiers and inputs. We also found that for these tasks, the level of generality obtained by Fox-cs in the portion of population that produces optimal behaviour is consistent with Wilson's generality hypothesis.