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IWSOS
2011
Springer
14 years 12 days ago
Evolving Self-organizing Cellular Automata Based on Neural Network Genotypes
Abstract This paper depicts and evaluates an evolutionary design process for generating a complex self-organizing multicellular system based on Cellular Automata (CA). We extend th...
Wilfried Elmenreich, István Fehérv&a...
UAI
2003
14 years 11 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
GECCO
2007
Springer
172views Optimization» more  GECCO 2007»
15 years 3 months ago
Acquiring evolvability through adaptive representations
Adaptive representations allow evolution to explore the space of phenotypes by choosing the most suitable set of genotypic parameters. Although such an approach is believed to be ...
Joseph Reisinger, Risto Miikkulainen
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 1 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
66
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HICSS
2006
IEEE
128views Biometrics» more  HICSS 2006»
15 years 3 months ago
Should I Stay or Should I Go? Worker Commitment to Virtual Organizations
As society enters the twenty-first century there is a growing realization that information technology (IT) is heavily influencing organizational structures [1]. One such structure...
Yulin Fang, Derrick J. Neufeld