Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Top-down induction of first-order logical decision trees
Artificial Intelligence
Artificial Intelligence
Relational reinforcement learning
Machine Learning - Special issue on inducive logic programming
Machine Learning
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Learning Logical Definitions from Relations
Machine Learning
Proceedings of the Genetic and Evolutionary Computation Conference
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Accuracy-based Neuro And Neuro-fuzzy Classifier Systems
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Get Real! XCS with Continuous-Valued Inputs
Learning Classifier Systems, From Foundations to Applications
An Algorithmic Description of XCS
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Detecting Traffic Problems with ILP
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
For real! XCS with continuous-valued inputs
Evolutionary Computation
Strong, Stable, and Reliable Fitness Pressure in XCS due to Tournament Selection
Genetic Programming and Evolvable Machines
Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetic and Evolutionary Computation Conference
Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetic and Evolutionary Computation Conference
Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetic and Evolutionary Computation Conference
A first order logic classifier system
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Kernel-based, ellipsoidal conditions in the real-valued XCS classifier system
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
XCS with computed prediction in multistep environments
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Rule-based evolutionary online learning systems: learning bounds, classification, and prediction
Rule-based evolutionary online learning systems: learning bounds, classification, and prediction
Combining model-based and instance-based learning for first order regression
ICML '05 Proceedings of the 22nd international conference on Machine learning
Classifier fitness based on accuracy
Evolutionary Computation
Toward a theory of generalization and learning in XCS
IEEE Transactions on Evolutionary Computation
BRA: An Algorithm for Simulating Bounded Rational Agents
Computational Economics
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This article describes a learning classifier system (LCS) approach to relational reinforcement learning (RRL). The system, Foxcs-2, is a derivative of Xcsthat learns rules expressed as definite clauses over first-order logic. By adopting the LCS approach, Foxcs-2, unlike many RRL systems, is a general, model-free and "tabula rasa" system. The change in representation from bit-strings in Xcsto first-order logic in Foxcs-2necessitates modifications, described within, to support matching, covering, mutation and several other functions. Evaluation on inductive logic programming (ILP) and RRL tasks shows that the performance of Foxcs-2is comparable to other systems. Further evaluation on RRL tasks highlights a significant advantage of Foxcs-2's rule language: in some environments it is able to represent policies that are genuinely scalable; that is, policies that are independent of the size of the environment.