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GPEM
2006
161views more  GPEM 2006»
14 years 9 months ago
Solving differential equations with genetic programming
A novel method for solving ordinary and partial differential equations, based on grammatical evolution is presented. The method forms generations of trial solutions expressed in an...
Ioannis G. Tsoulos, Isaac E. Lagaris
GECCO
2009
Springer
112views Optimization» more  GECCO 2009»
15 years 4 months ago
Soft memory for stock market analysis using linear and developmental genetic programming
Recently, a form of memory usage was introduced for genetic programming (GP) called “soft memory.” Rather than have a new value completely overwrite the old value in a registe...
Garnett Carl Wilson, Wolfgang Banzhaf
GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
15 years 4 months ago
Genetically programmed learning classifier system description and results
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
Gregory Anthony Harrison, Eric W. Worden
GECCO
2004
Springer
15 years 3 months ago
Multi-agent Cooperation Using Genetic Network Programming with Automatically Defined Groups
In this paper, we propose a genetic network programming (GNP) architecture using a coevolution model called automatically defined groups (ADG). The GNP evolves networks for describ...
Tadahiko Murata, Takashi Nakamura
CORR
2006
Springer
153views Education» more  CORR 2006»
14 years 9 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...