Induction: processes of inference, learning, and discovery
Induction: processes of inference, learning, and discovery
Classifier systems and genetic algorithms
Artificial Intelligence
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Adding temporary memory to ZCS
Adaptive Behavior
Understanding intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Robot Shaping: An Experiment in Behavior Engineering
Robot Shaping: An Experiment in Behavior Engineering
Classifiers that approximate functions
Natural Computing: an international journal
Evolving Robot Behaviours with Diffusing Gas Networks
Proceedings of the First European Workshop on Evolutionary Robotics
The Emergence of Default Hierarchies in Learning Classifier Systems
Proceedings of the 3rd International Conference on Genetic Algorithms
TCS Learning Classifier System Controller on a Real Robot
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Latent Learning and Action Planning in Robots with Anticipatory Classifier Systems
Learning Classifier Systems, From Foundations to Applications
An Introduction to Learning Fuzzy Classifier Systems
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
YACS: Combining Dynamic Programming with Generalization in Classifier Systems
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Strength or Accuracy: Credit Assignment in Learning Classifier Systems
Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
Applications of Learning Classifier Systems
Applications of Learning Classifier Systems
Toward Optimal Classifier System Performance in Non-Markov Environments
Evolutionary Computation
Zcs: A zeroth level classifier system
Evolutionary Computation
Classifier fitness based on accuracy
Evolutionary Computation
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There are few contributions to robot autonomous navigation applying Learning Classifier Systems (LCS) to date. The primary objective of this work is to analyse the performance of the strength-based LCS and the accuracy-based LCS, named EXtended Learning Classifier System (XCS), when applied to two distinct robotic tasks. The first task is purely reactive, which means that the action to be performed can rely only on the current status of the sensors. The second one is non-reactive, which means that the robot might use some kind of memory to be able to deal with aliasing states. This work presents a rule evolution analysis, giving examples of evolved populations and their peculiarities for both systems. A review of LCS derivatives in robotics is provided together with a discussion of the main findings and an outline of future investigations.