Exploring the Power of Genetic Search in Learning Symbolic Classifiers
IEEE Transactions on Pattern Analysis and Machine Intelligence
Representational effects in a simple classifier system
SAC '94 Proceedings of the 1994 ACM symposium on Applied computing
Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
Autonomous Robots
A Theoretical Approach of an Intelligent Robot Gripper to Grasp Polygon Shaped Objects
Journal of Intelligent and Robotic Systems
Evolutionary Computation
Self-Adaptive Mutation in ZCS Controllers
Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
Robot Learning Using Gate-Level Evolvable Hardware
EWLR-6 Proceedings of the 6th European Workshop on Learning Robots
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
Learning Classifier Systems Applied to Knowledge Discovery in Clinical Research Databases
Learning Classifier Systems, From Foundations to Applications
A Learning Classifier Systems Bibliography
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 Self-Adaptive Classifier System
IWLCS '00 Revised Papers from the Third International Workshop on Advances in Learning Classifier Systems
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
A GP Artificial Ant for Image Processing: Preliminary Experiments with EASEA
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Recent trends in learning classifier systems research
Advances in evolutionary computing
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A Study of Structural and Parametric Learning in XCS
Evolutionary Computation
A probabilistic classifier system and its application in data mining
Evolutionary Computation
Genetic Programming and Evolvable Machines
Collective behavior based hierarchical XCS
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Searching for diverse, cooperative populations with genetic algorithms
Evolutionary Computation
Zcs: A zeroth level classifier system
Evolutionary Computation
Is a learning classifier system a type of neural network?
Evolutionary Computation
Implicit niching in a learning classifier system: Nature's way
Evolutionary Computation
Using coverage as a model building constraint in learning classifier systems
Evolutionary Computation
Classifier fitness based on accuracy
Evolutionary Computation
Search-intensive concept induction
Evolutionary Computation
An analysis of generalization in the xcs classifier system
Evolutionary Computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Learning Classifier Systems: Looking Back and Glimpsing Ahead
Learning Classifier Systems
Natural niching for evolving cooperative classifiers
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Journal of Artificial Intelligence Research
Learning DNF by decision trees
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Learning novel domains through curiosity and conjecture
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Alternatives for classifier system credit assignment
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Hierarchical genetic algorithms operating on populations of computer programs
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Hierarchical credit allocation in a classifier system
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Learning classifier systems: a complete introduction, review, and roadmap
Journal of Artificial Evolution and Applications
Imitation as a mechanism of cultural transmission
Artificial Life
Genetic algorithms and artificial life
Artificial Life
Use of learning classifier system for inferring natural language grammar
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
XCS for personalizing desktop interfaces
IEEE Transactions on Evolutionary Computation
Complementary discrimination learning: a duality between generalization and discrimination
AAAI'90 Proceedings of the eighth National conference on Artificial intelligence - Volume 2
COGIN: symbolic induction with genetic algorithms
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Learning Classification Programs: The Genetic Algorithm Approach
Fundamenta Informaticae
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This paper characterizes and investigates, from the perspective of machine learning and, particularly, classifier systems, the learning problem faced by animals and autonomous robots (here collectively termed animats). We suggest that, to survive in their environments, animats must in effect learn multiple disjunctive concepts incrementally under payoff (needs-satisfying) feedback. A review of machine learning techniques indicates that most relax at least one of these constraints. In theory, classifier systems satisfy the constraints, but tests have been limited. We show how the standard classifier system model applies to the animat learning problem. Then, in the experimental part of the paper, we specialize the model and test it in a problem environment satisfying the constraints and consisting of a difficult, disjunctive Boolean function drawn from the machine learning literature. Results include: learning the function in significantly fewer trials than a neural-network method; learning under payoff regimes that include both noisy payoff and partial reward for suboptimal performance; demonstration, in a classifier system, of a theoretically predicted property of genetic algorithms: the superiority of crossovers to point mutations; and automatic control of variation (search) rate based on system entropy. We conclude that the results support the classifier system approach to the animat problem, but suggest work aimed at the emergence of behavioral hierarchies of classifiers to offset slower learning rates in larger problems.