Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
Classifier systems and genetic algorithms
Artificial Intelligence
Proceedings of the seventh international conference (1990) on Machine learning
Lookahead planning and latent learning in a classifier system
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Toward a Model of Intelligence as an Economy of Agents
Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
The anticipatory classifier system and genetic generalization
Natural Computing: an international journal
Classifier Systems and the Animat Problem
Machine Learning
Evolutionary Computation
Learning Classifier Systems, From Foundations to Applications
Learning Classifier Systems, From Foundations to Applications
Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
Knowledge Growth in an Artificial Animal
Proceedings of the 1st International Conference on Genetic Algorithms
Properties of the Bucket Brigade
Proceedings of the 1st International Conference on Genetic Algorithms
Improving the Performance of Genetic Algorithms in Classifier Systems
Proceedings of the 1st International Conference on Genetic Algorithms
Accuracy-based Neuro And Neuro-fuzzy Classifier Systems
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
An Introduction to Learning Fuzzy Classifier Systems
Learning Classifier Systems, From Foundations to Applications
An Algorithmic Description of ACS2
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
Do We Really Need to Estimate Rule Utilities in Classifier Systems?
Learning Classifier Systems, From Foundations to Applications
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
A learning system based on genetic adaptive algorithms
A learning system based on genetic adaptive algorithms
Intelligent behavior as an adaptation to the task environment
Intelligent behavior as an adaptation to the task environment
Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Applications of Learning Classifier Systems
Applications of Learning Classifier Systems
Toward Optimal Classifier System Performance in Non-Markov Environments
Evolutionary Computation
Classifier prediction based on tile coding
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Learning classifier systems: a survey
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Zcs: A zeroth level classifier system
Evolutionary Computation
Classifier fitness based on accuracy
Evolutionary Computation
Design and Analysis of Learning Classifier Systems: A Probabilistic Approach (Studies in Computational Intelligence)
Context-dependent predictions and cognitive arm control with XCSF
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Evolutionary rule-based systems for imbalanced data sets
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary and Metaheuristics based Data Mining (EMBDM); Guest Editors: José A. Gámez, María J. del Jesús, José M. Puerta
Learning sensorimotor control structures with XCSF: redundancy exploitation and dynamic control
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Anticipatory Learning Classifier Systems and Factored Reinforcement Learning
Anticipatory Behavior in Adaptive Learning Systems
Facetwise analysis of XCS for problems with class imbalances
IEEE Transactions on Evolutionary Computation
Controlling a four degree of freedom arm in 3D using the XCSF learning classifier system
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Resource management and scalability of the XCSF learning classifier system
Theoretical Computer Science
Toward a theory of generalization and learning in XCS
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
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In the 1970s, John H. Holland designed Learning Classifier Systems (LCSs) as highly adaptive, cognitive systems. Since the introduction of the accuracy-based XCS classifier system by Stewart W. Wilson in 1995 and the modular analysis of several LCSs thereafter, LCSs have become a state-of-the-art machine learning system. Various publications have shown that LCSs can effectively solve data-mining problems, reinforcement learning problems, other predictive problems, and even cognitive, robotics control problems. In comparison to other, non-evolutionary machine learning techniques, it was shown that performance is competitive or even superior, dependent on the setup and problem. Advantages are that LCSs are learning online, are very plastic and flexible, are applicable to a larger range of problems, and are highly adaptive. Moreover, system knowledge can be easily extracted, visualized, or even used to focus the progressive search on particular interesting subspaces. The Learning Classifier System tutorial provides a gentle introduction to LCSs and their general functionality. It then surveys the current theoretical understanding of the systems. Finally, we provide a suite of current successful LCS applications and discuss the most promising areas for future applications and research directions.