872 search results - page 124 / 175 » Evolving Complex Neural Networks |
GECCO
2006
Springer
15 years 1 months ago
2006
Springer
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
103
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GECCO
2008
Springer
14 years 11 months ago
2008
Springer
In this work we present a new methodology for structure and parameter estimation in cell systems biology modelling. Our modelling framework is based on P systems, an unconl comput...
82
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ICC
2009
IEEE
15 years 4 months ago
2009
IEEE
—At present there is a strong worldwide push toward bringing fiber closer to individual homes and businesses. Another evolutionary step is the cost-effective all-optical integra...
144
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GECCO
2007
Springer
15 years 4 months ago
2007
Springer
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
MIDDLEWARE
2004
Springer
15 years 3 months ago
2004
Springer
Recent evolution in computer networks clearly demonstrates a trend towards complex and dynamic networks. To fully exploit the potential of such heterogeneous and rapidly evolving ...