95 search results - page 6 / 19 » Using context-aware crossover to improve the performance of ... |
GECCO
2006
Springer
15 years 1 months ago
2006
Springer
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
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EPS
1998
Springer
15 years 1 months ago
1998
Springer
Abstract. In this paper we describe EvoCK, a new approach to the application of genetic programming (GP) to planning. This approach starts with a traditional AI planner (PRODIGY)an...
GECCO
2004
Springer
15 years 3 months ago
2004
Springer
Extending the notion of inheritable genotype in genetic programming (GP) from the common model of DNA into chromatin (DNA and histones), we propose an approach of embedding in GP a...
GECCO
2004
Springer
15 years 3 months ago
2004
Springer
This paper describes POPE-GP, a system that makes use of the NSGA-II multiobjective evolutionary algorithm as an alternative, parameter-free technique for eliminating program bloat...
ICMLA
2007
14 years 11 months ago
2007
Gene Expression Programming (GEP) is an evolutionary algorithm that incorporates both the idea of a simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and...