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GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
16 years 24 days ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
16 years 24 days ago
Nonlinear dynamics modelling for controller evolution
The problem of how to acquire a model of a physical robot, which is fit for evolution of controllers that can subsequently be used to control that robot, is considered in the con...
Julian Togelius, Renzo De Nardi, Hugo Gravato Marq...
GECCO
2007
Springer
228views Optimization» more  GECCO 2007»
16 years 24 days ago
Collective behavior based hierarchical XCS
This paper attempts to extend the XCS research by analyzing the impact of information exchange between XCS agents on classifier performance. Two types of information are exchange...
Matthew Gershoff, Sonia Schulenburg
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
16 years 24 days ago
Exploiting multiple robots to accelerate self-modeling
In previous work [8] a computational framework was demonstrated that allows a mobile robot to autonomously evolve models its own body for the purposes of adaptive behavior generat...
Josh C. Bongard
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
16 years 24 days ago
The effect of learning on life history evolution
A series of evolutionary neural network simulations are presented which explore the hypothesis that learning factors can result in the evolution of long periods of parental protec...
John A. Bullinaria
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