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IWANN
2001
Springer
13 years 12 months ago
Introducing Multi-objective Optimization in Cooperative Coevolution of Neural Networks
Nicolás García-Pedrajas, Eloy Sanz-T...
ECAL
2005
Springer
14 years 29 days ago
(Co)Evolution of (De)Centralized Neural Control for a Gravitationally Driven Machine
Using decentralized control structures for robot control can offer a lot of advantages, such as less complexity, better fault tolerance and more flexibility. In this paper the ev...
Steffen Wischmann, Martin Hülse, Frank Pasema...
PPSN
1994
Springer
13 years 11 months ago
A Cooperative Coevolutionary Approach to Function Optimization
A general model for the coevolution of cooperating species is presented. This model is instantiated and tested in the domain of function optimization, and compared with a tradition...
Mitchell A. Potter, Kenneth A. De Jong
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 29 days ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
13 years 8 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...