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» Metaphor for learning: an evolutionary algorithm
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GECCO
2000
Springer
101views Optimization» more  GECCO 2000»
13 years 11 months ago
Evolutionary Design of Behaviors for Action-Based Environment Modeling by a Mobile Robot
This paper describes an evolutionary way to acquire behaviors of a mobile robot for recognizing environments. We have proposed AEM (Action-based Environment Modeling) approach for...
Seiji Yamada
GECCO
2005
Springer
220views Optimization» more  GECCO 2005»
14 years 1 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
GECCO
2008
Springer
177views Optimization» more  GECCO 2008»
13 years 8 months ago
Reduced computation for evolutionary optimization in noisy environment
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...
Maumita Bhattacharya
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
14 years 1 months ago
Population-based incremental learning with memory scheme for changing environments
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
Shengxiang Yang
GECCO
2007
Springer
181views Optimization» more  GECCO 2007»
14 years 1 months ago
A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation
Surrogate-Assisted Memetic Algorithm(SAMA) is a hybrid evolutionary algorithm, particularly a memetic algorithm that employs surrogate models in the optimization search. Since mos...
Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendh...