Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
Technical Note: \cal Q-Learning
Machine Learning
Properties of the Bucket Brigade
Proceedings of the 1st International Conference on Genetic Algorithms
An Introduction to Anticipatory Classifier Systems
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
Zcs: A zeroth level classifier system
Evolutionary Computation
Classifier fitness based on accuracy
Evolutionary Computation
A Bigger Learning Classifier Systems Bibliography
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
An Algorithmic Description of ACS2
IWLCS '01 Revised Papers from the 4th International Workshop on Advances in Learning Classifier Systems
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The Anticipatory Classifier System (ACS) recently showed many capabilities new to the Learning Classifier System field. Due to its enhanced rule structure with an effect part, it forms an internal environmental representation, learns latently besides the common reward learning, and can use many cognitive processes. This paper introduces a probability-enhancement in the predictions of the ACS which enables the system to handle different kinds of non-determinism in an environment. Experiments in two different mazes will show that the ACS is now able to handle action-noise and irrelevant random attributes in the perceptions. Furthermore, applications with a recently introduced GA will reveal the general independence of the two new mechanism as well as the ability of the GA to substantially decrease the population size.