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81
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GECCO
2007
Springer
164views Optimization» more  GECCO 2007»
15 years 4 months ago
Learning building block structure from crossover failure
In the classical binary genetic algorithm, although crossover within a building block (BB) does not always cause a decrease in fitness, any decrease in fitness results from the ...
Zhenhua Li, Erik D. Goodman
68
Voted
GECCO
2007
Springer
143views Optimization» more  GECCO 2007»
15 years 4 months ago
Learning and exploiting knowledge in multi-agent task allocation problems
Imagine a group of cooperating agents attempting to allocate tasks amongst themselves without knowledge of their own capabilities. Over time, they develop a belief of their own sk...
Adam Campbell, Annie S. Wu
GECCO
2007
Springer
180views Optimization» more  GECCO 2007»
15 years 4 months 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
73
Voted
GECCO
2007
Springer
176views Optimization» more  GECCO 2007»
15 years 4 months 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
76
Voted
GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
15 years 4 months ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifical...
Robert Elliott Smith, Max Kun Jiang