Communications of the ACM
Inductive learning of decision rules from attribute-based examples: a knowledge-intensive genetic algorithm approach
An introduction to computational learning theory
An introduction to computational learning theory
Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
SIA: A Supervised Inductive Algorithm with Genetic Search for Learning Attributes based Concepts
ECML '93 Proceedings of the European Conference on Machine Learning
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
Strong, Stable, and Reliable Fitness Pressure in XCS due to Tournament Selection
Genetic Programming and Evolvable Machines
Analysis of the initialization stage of a Pittsburgh approach learning classifier system
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
The compact classifier system: motivation, analysis, and first results
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Smart crossover operator with multiple parents for a Pittsburgh learning classifier system
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Studying XCS/BOA learning in Boolean functions: structure encoding and random Boolean functions
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Prediction update algorithms for XCSF: RLS, Kalman filter, and gain adaptation
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Automated global structure extraction for effective local building block processing in XCS
Evolutionary Computation
Classifier fitness based on accuracy
Evolutionary Computation
Learning concept classification rules using genetic algorithms
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 2
IWLCS'03-05 Proceedings of the 2003-2005 international conference on Learning classifier systems
IEEE Transactions on Evolutionary Computation
Toward a theory of generalization and learning in XCS
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
A tutorial for competent memetic algorithms: model, taxonomy, and design issues
IEEE Transactions on Evolutionary Computation
Fuzzy-XCS: A Michigan Genetic Fuzzy System
IEEE Transactions on Fuzzy Systems
A mixed discrete-continuous attribute list representation for large scale classification domains
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Large scale data mining using genetics-based machine learning
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
An unorthodox introduction to Memetic Algorithms
ACM SIGEVOlution
Random artificial incorporation of noise in a learning classifier system environment
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Large scale data mining using genetics-based machine learning
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
A parallel genetic programming algorithm for classification
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
Information Sciences: an International Journal
Post-processing operators for decision lists
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Large scale data mining using genetics-based machine learning
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Large scale data mining using genetics-based machine learning
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
An interpretable classification rule mining algorithm
Information Sciences: an International Journal
Improving the performance of the BioHEL learning classifier system
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
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In this paper we empirically evaluate several local search (LS) mechanisms that heuristically edit classification rules and rule sets to improve their performance. Two kinds of operators are studied, (1) rule-wise operators, which edit individual rules, and (2) a rule set-wise operator, which takes the rules from N parents (N ≥ 2) to generate a new offspring, selecting the minimum subset of candidate rules that obtains maximum training accuracy. Moreover, various ways of integrating these operators within the evolutionary cycle of learning classifier systems are studied. The combinations of LS operators and policies are integrated in a Pittsburgh approach framework that we call MPLCS for memetic Pittsburgh learning classifier system. MPLCS is systematically evaluated using various metrics. Several datasets were employed with the objective of identifying which combination of operators and policies scale well, are robust to noise, generate compact solutions, and use the least amount of computational resources to solve the problems.