Classifier systems and genetic algorithms
Artificial Intelligence
Applying genetics to fuzzy logic
AI Expert
Technical Note: \cal Q-Learning
Machine Learning
Reinforcement learning with replacing eligibility traces
Machine Learning - Special issue on reinforcement learning
Evolving fuzzy rule based controllers using genetic algorithms
Fuzzy Sets and Systems
Fuzzy set theory: foundations and applications
Fuzzy set theory: foundations and applications
Anytime learning and adaptation of structured fuzzy behaviors
Adaptive Behavior - Special issue on environment structure and behavior
Genetic Algorithms and Soft Computing
Genetic Algorithms and Soft Computing
Robot Shaping: An Experiment in Behavior Engineering
Robot Shaping: An Experiment in Behavior Engineering
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Classifier Systems that Learn Internal World Models
Machine Learning
Properties of the Bucket Brigade
Proceedings of the 1st International Conference on Genetic Algorithms
Dynamic Control of Genetic Algorithms Using Fuzzy Logic Techniques
Proceedings of the 5th International Conference on Genetic Algorithms
Fuzzy Network Synthesis with Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
A New Approach to Fuzzy Classifier Systems
Proceedings of the 5th International Conference on Genetic Algorithms
Controlling Excessive Fuzziness in a Fuzzy Classifier System
Proceedings of the 5th International Conference on Genetic Algorithms
Fuzzy and Crisp Representations of Real-Valued Input for Learning Classifier Systems
Learning Classifier Systems, From Foundations to Applications
Genetic Algorithms for the Development of Fuzzy Controllers for Mobile Robots
Selected papers from the IEEE/Nagoya-University World Wisepersons Workshop on Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms,
Selected papers from the IEEE/Nagoya-University World Wisepersons Workshop on Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms,
A Fuzzy Classifier System That Generates Linguistic Rules for Pattern Classification Problems
Selected papers from the EEE/Nagoya-University World Wisepersons Workshop on Fuzzy Logic, Neural Networks, and Evolutionary Computation
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
Classifier fitness based on accuracy
Evolutionary Computation
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
New techniques for genetic development of a class of fuzzy controllers
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Generating fuzzy rules for target tracking using a steady-stategenetic algorithm
IEEE Transactions on Evolutionary Computation
On Using Constructivism in Neural Classifier Systems
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
First Results from Experiments in Fuzzy Classifier System Architectures for Mobile Robotics
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
A Bigger Learning Classifier Systems Bibliography
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Analysing Learning Classifier Systems in Reactive and Non-reactive Robotic Tasks
Learning Classifier Systems
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
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
To handle real valued input in XCS: using fuzzy hyper-trapezoidal membership in classifier condition
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Towards final rule set reduction in XCS: a fuzzy representation approach
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Development of a genetic fuzzy controller for an unmanned aerial vehicle
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
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We present a class of Learning Classifier Systems that learn fuzzy rule-based models, instead of interval-based or Boolean models. We discuss some motivations to consider Learning Fuzzy Classifier Systems (LFCS) as a promising approach to learn mappings from real-valued input to real-valued output, basing on data interpretation implemented by fuzzy sets. We describe some of the approaches explicitly or implicitly referring to this research area, presented in literature since the beginning of the last decade. We also show how the general LFCS model can be considered as a framework for a wide range of systems, each implementing in a different way the modules composing the basic architecture. We also mention some of the applications of LFCS presented in literature, which show the potentialities of this type of systems. Finally, we introduce a general methodology to extend reinforcement distribution algorithms usually not designed to learn fuzzy models. This opens new application possibilities.