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CIG
2005
IEEE
13 years 11 months ago
Forcing Neurocontrollers to Exploit Sensory Symmetry Through Hard-wired Modularity in the Game of Cellz
Several attempts have been made in the past to construct encoding schemes that allow modularity to emerge in evolving systems, but success is limited. We believe that in order to c...
Julian Togelius, Simon M. Lucas
GECCO
2004
Springer
155views Optimization» more  GECCO 2004»
13 years 10 months ago
Genetic Network Programming with Reinforcement Learning and Its Performance Evaluation
A new graph-based evolutionary algorithm named “Genetic Network Programming, GNP” has been proposed. GNP represents its solutions as directed graph structures, which can improv...
Shingo Mabu, Kotaro Hirasawa, Jinglu Hu
TEC
2008
139views more  TEC 2008»
13 years 5 months ago
Genetic Programming Approaches for Solving Elliptic Partial Differential Equations
In this paper, we propose a technique based on genetic programming (GP) for meshfree solution of elliptic partial differential equations. We employ the least-squares collocation pr...
Andras Sobester, Prasanth B. Nair, Andy J. Keane
GECCO
2005
Springer
175views Optimization» more  GECCO 2005»
13 years 10 months ago
Nonlinear feature extraction using a neuro genetic hybrid
Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
Yung-Keun Kwon, Byung Ro Moon
ML
2000
ACM
244views Machine Learning» more  ML 2000»
13 years 5 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski