Results 1 - 10 of 27,576

Decision Combination in Multiple Classifier Systems

by Tin Kam Ho, Jonathan J. Hull, Sargur N. Srihari - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 16. NO. I. JANUARY 1994 , 1994
"... A multiple classifier system is a powerful solution to difficult pattern recognition problems involving large class sets and noisy input because it allows simultaneous use of arbitrary feature descriptors and classification procedures. Decisions by the classifiers can be represented as rankings of ..."
Abstract - Cited by 377 (5 self) - Add to MetaCart
A multiple classifier system is a powerful solution to difficult pattern recognition problems involving large class sets and noisy input because it allows simultaneous use of arbitrary feature descriptors and classification procedures. Decisions by the classifiers can be represented as rankings

Classifier Systems

by Gilles Enee, Cathy Escazut, Gilles Enee, Cathy Escazut , 2015
"... Classifier systems evolving multi-agent system with distributed elitism ..."
Abstract - Add to MetaCart
Classifier systems evolving multi-agent system with distributed elitism

Classifier systems and the animat problem

by Stewart W. Wilson - Machine Learning , 1987
"... animal learning, genetic algorithm Abstract. 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 ..."
Abstract - Cited by 86 (5 self) - Add to MetaCart
animal learning, genetic algorithm Abstract. 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

Generalization in the XCS Classifier System

by S. W. Wilson , 1998
"... This paper studies two changes to XCS, a classifier system in which fitness is based on prediction accuracy and the genetic algorithm takes place in environmental niches. The changes were aimed at increasing XCS's tendency to evolve accurate, maximally general classifiers and were tested o ..."
Abstract - Cited by 86 (11 self) - Add to MetaCart
This paper studies two changes to XCS, a classifier system in which fitness is based on prediction accuracy and the genetic algorithm takes place in environmental niches. The changes were aimed at increasing XCS's tendency to evolve accurate, maximally general classifiers and were tested

Design Of Multiple Classifier Systems

by Fabio Roli, Giorgio Giacinto
"... Introduction In the past decade, a number of papers 19,28 have proposed the combination of multiple classifiers for designing high performance pattern classification systems. The rationale behind the growing interest in multiple classifier systems (MCSs) is that the classical approach to designing a ..."
Abstract - Cited by 47 (0 self) - Add to MetaCart
Introduction In the past decade, a number of papers 19,28 have proposed the combination of multiple classifiers for designing high performance pattern classification systems. The rationale behind the growing interest in multiple classifier systems (MCSs) is that the classical approach to designing

Representational Difficulties With Classifier Systems

by Dale Schuurmans, Jonathan Schaeffer - in Proceedings Third International Conference on Genetic Algorithms , 1989
"... Classifier systems are currently in vogue as a way of using genetic algorithms to demonstrate machine learning. However, there are a number of difficulties with the formalization that can influence how knowledge is represented and the rate at which the system can learn. Some of the problems are inhe ..."
Abstract - Cited by 14 (0 self) - Add to MetaCart
Classifier systems are currently in vogue as a way of using genetic algorithms to demonstrate machine learning. However, there are a number of difficulties with the formalization that can influence how knowledge is represented and the rate at which the system can learn. Some of the problems

Function Approximation with a Classifier System

by Stewart W. Wilson - IN , 2001
"... A classifier system, XCSF, is introduced in which the prediction estimation mechanism is used to learn approximations to functions. The addition ..."
Abstract - Cited by 45 (4 self) - Add to MetaCart
A classifier system, XCSF, is introduced in which the prediction estimation mechanism is used to learn approximations to functions. The addition

Connectionist Learning Classifier System

by Alexey Vasilyev - In Proc. of Traditional And Innovations In Sustainable Development Of Society, Rezekne , 2002
"... Impetuous development of artificial neural networks makes it possible to transfer many ideas from this area into adjacent areas. This work investigates an opportunity of mapping learning classifier systems (LCS) into artificial neural networks (ANN). Possible learning types for hybrid connectionist ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
Impetuous development of artificial neural networks makes it possible to transfer many ideas from this area into adjacent areas. This work investigates an opportunity of mapping learning classifier systems (LCS) into artificial neural networks (ANN). Possible learning types for hybrid connectionist

Connectionist Learning Classifier System

by Alexey Vasilyev Transport, Alexey Vasilyev - In Proc. of Traditional And Innovations In Sustainable Development Of Society, Rezekne , 2002
"... Impetuous development of artificial neural networks makes it possible to transfer many ideas from this area into adjacent areas. This work investigates an opportunity of mapping learning classifier systems (LCS) into artificial neural networks (ANN). Possible learning types for hybrid connectionist ..."
Abstract - Add to MetaCart
Impetuous development of artificial neural networks makes it possible to transfer many ideas from this area into adjacent areas. This work investigates an opportunity of mapping learning classifier systems (LCS) into artificial neural networks (ANN). Possible learning types for hybrid connectionist

VCS: Variable Classifier System

by Lingyan Shu , Jonathan Schaeffer - George Mason University , 1989
"... ABSTRACT Classifier systems (CS) have proven to be useful tools for the study of genetic algorithm based learning. Unfortunately, there are a number of difficulties with the formalization that limit the representational capabilities and, hence, its problem solving abilities and the speed at which i ..."
Abstract - Cited by 4 (0 self) - Add to MetaCart
ABSTRACT Classifier systems (CS) have proven to be useful tools for the study of genetic algorithm based learning. Unfortunately, there are a number of difficulties with the formalization that limit the representational capabilities and, hence, its problem solving abilities and the speed at which
Results 1 - 10 of 27,576