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» Evolutionary Computation for Modeling and Optimization
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GECCO
2003
Springer
14 years 2 months ago
Effective Use of Directional Information in Multi-objective Evolutionary Computation
While genetically inspired approaches to multi-objective optimization have many advantages over conventional approaches, they do not explicitly exploit directional/gradient informa...
Martin Brown, Robert E. Smith
ROBIO
2006
IEEE
123views Robotics» more  ROBIO 2006»
14 years 2 months ago
Evolutionary Robotics, Anticipation and the Reality Gap
— Evolutionary Robotics provide efficient tools and approach to address automatic design of controllers for automous mobile robots. However, the computational cost of the optimi...
Cédric Hartland, Nicolas Bredeche
EC
2006
136views ECommerce» more  EC 2006»
13 years 8 months ago
Error Thresholds in Genetic Algorithms
The error threshold of replication is an important notion of the quasispecies evolution model; it is a critical mutation rate (error rate) beyond which structures obtained by an e...
Gabriela Ochoa
GECCO
2010
Springer
154views Optimization» more  GECCO 2010»
14 years 1 months ago
Evolutionary learning in networked multi-agent organizations
This study proposes a simple computational model of evolutionary learning in organizations informed by genetic algorithms. Agents who interact only with neighboring partners seek ...
Jae-Woo Kim
GECCO
1999
Springer
145views Optimization» more  GECCO 1999»
14 years 1 months ago
Three Ways to Grow Designs: A Comparison of Embryogenies for an Evolutionary Design Problem
This paper explores the use of growth processes, or embryogenies, to map genotypes to phenotypes within evolutionary systems. Following a summary of the significant features of em...
Peter J. Bentley, Sanjeev Kumar