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ICANN
2009
Springer
13 years 11 months ago
Measuring and Optimizing Behavioral Complexity for Evolutionary Reinforcement Learning
Model complexity is key concern to any artificial learning system due its critical impact on generalization. However, EC research has only focused phenotype structural complexity ...
Faustino J. Gomez, Julian Togelius, Jürgen Sc...
ECAL
2005
Springer
13 years 10 months ago
The Quantitative Law of Effect is a Robust Emergent Property of an Evolutionary Algorithm for Reinforcement Learning
An evolutionary reinforcement-learning algorithm, the operation of which was not associated with an optimality condition, was instantiated in an artificial organism. The algorithm ...
J. J. McDowell, Zahra Ansari
GECCO
2006
Springer
175views Optimization» more  GECCO 2006»
13 years 8 months ago
A computational theory of adaptive behavior based on an evolutionary reinforcement mechanism
Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
J. J. McDowell, Paul L. Soto, Jesse Dallery, Saule...
GECCO
2005
Springer
220views Optimization» more  GECCO 2005»
13 years 10 months ago
Scale invariant pareto optimality: a meta--formalism for characterizing and modeling cooperativity in evolutionary systems
This article describes a mathematical framework for characterizing cooperativity in complex systems subject to evolutionary pressures. This framework uses three foundational compo...
Mark Fleischer
PRL
2006
148views more  PRL 2006»
13 years 4 months ago
An agent based evolutionary approach to path detection for off-road vehicle guidance
This paper describes an ant colony optimization approach adopted to decide on road-borders to automatically guide a vehicle developed for the DARPA Grand Challenge 2004, available...
Alberto Broggi, Stefano Cattani