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FOGA
2011
12 years 8 months ago
Computational complexity analysis of simple genetic programming on two problems modeling isolated program semantics
Analyzing the computational complexity of evolutionary algorithms (EAs) for binary search spaces has significantly informed our understanding of EAs in general. With this paper, ...
Greg Durrett, Frank Neumann, Una-May O'Reilly
GECCO
2010
Springer
182views Optimization» more  GECCO 2010»
13 years 9 months ago
Model selection in genetic programming
Abstract. We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We pre...
Cruz E. Borges, César Luis Alonso, Jos&eacu...
GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
13 years 8 months ago
Characterizing a Tunably Difficult Problem in Genetic Programming
This paper examines the behavioral phenomena that occur with the tuning of the binomial-3 problem. Our analysis identifies a distinct set of phenomena that may be generalizable to...
Omer A. Chaudhri, Jason M. Daida, Jonathan C. Khoo...
WCE
2007
13 years 6 months ago
Game Theory Using Genetic Algorithms
—In this paper we used genetic algorithms to1 find the solution of game theory. We proposed new method foe solving game theory and find the optimal strategy for player A or playe...
Ismail A. Ismail, Nabawia A. El Ramly, M. M. El Ka...
AIIA
1995
Springer
13 years 8 months ago
Learning Programs in Different Paradigms using Genetic Programming
Genetic Programming (GP) is a method of automatically inducing programs by representing them as parse trees. In theory, programs in any computer languages can be translated to par...
Man Leung Wong, Kwong-Sak Leung