Adding temporary memory to ZCS
Adaptive Behavior
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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
Zcs: A zeroth level classifier system
Evolutionary Computation
Memory exploitation in learning classifier systems
Evolutionary Computation
What Is a Learning Classifier System?
Learning Classifier Systems, From Foundations to Applications
Latent Learning and Action Planning in Robots with Anticipatory Classifier Systems
Learning Classifier Systems, From Foundations to Applications
A Roadmap to the Last Decade of Learning Classifier System Research
Learning Classifier Systems, From Foundations to Applications
A Bigger Learning Classifier Systems Bibliography
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Probability-Enhanced Predictions in the Anticipatory Classifier System
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Biasing Exploration in an Anticipatory Learning Classifier System
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
Two Views of Classifier Systems
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
Grammar-Based Classifier System for Recognition of Promoter Regions
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Using the XCS classifier system for portfolio allocation of MSCI index component stocks
Expert Systems with Applications: An International Journal
A three-phase knowledge extraction methodology using learning classifier system
DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
An implementation of learning classifier systems for rule-based machine learning
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
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Anticipatory Classifier Systems (ACS) are classifier systems that learn by using the cognitive mechanism of anticipatory behavioral control which was introduced in cognitive psychology by Hoffmann [4]. They can learn in deterministic multi-step environments. A stepwise introduction to ACS is given. We start with the basic algorithm and apply it in simple "woods" environments. It will be shown that this algorithm can only learn in a special kind of deterministic multi-step environments. Two extensions are discussed. The first one enables an ACS to learn in any deterministic multistep environment. The second one allows an ACS to deal with a special kind of non-Markov state.