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ATAL
2006
Springer
15 years 3 months ago
Selecting informative actions improves cooperative multiagent learning
In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
Liviu Panait, Sean Luke
GECCO
2007
Springer
168views Optimization» more  GECCO 2007»
15 years 8 months ago
Evolutionary benefits of evolvable component integration
A system composed of multiple interacting components is capable of responding to contextual information and producing a higher range of non-linear responses to stimuli compared to...
David Malkin, R. Beau Lotto
GECCO
2008
Springer
107views Optimization» more  GECCO 2008»
15 years 3 months ago
The influence of scaling and assortativity on takeover times in scale-free topologies
In evolving systems, the topological characteristics of population structure have a pronounced impact on the rate of spread of advantageous alleles, and therefore affect selective...
Joshua L. Payne, Margaret J. Eppstein
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
15 years 3 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...
ACMICEC
2008
ACM
262views ECommerce» more  ACMICEC 2008»
15 years 3 months ago
Preventing information leakage between collaborating organisations
Information sharing and protection against leakage is a critical problem especially for organisations having sensitive information. Sharing content between individuals in the same...
Muntaha Alawneh, Imad M. Abbadi