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ML
1998
ACM
136views Machine Learning» more  ML 1998»
13 years 5 months ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
SEAL
1998
Springer
13 years 10 months ago
Robust Evolution Strategies
This paper empirically investigates the use and behaviour of Evolution Strategies (ES) algorithms on problems such as function optimisation and the use of evolutionary artificial ...
Kazuhiro Ohkura, Yoshiyuki Matsumura, Kanji Ueda
PPSN
2004
Springer
13 years 11 months ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
GECCO
2003
Springer
147views Optimization» more  GECCO 2003»
13 years 11 months ago
Optimal Elevator Group Control by Evolution Strategies
Abstract. Efficient elevator group control is important for the operation of large buildings. Recent developments in this field include the use of fuzzy logic and neural networks....
Thomas Beielstein, Claus-Peter Ewald, Sandor Marko...
BIODATAMINING
2008
147views more  BIODATAMINING 2008»
13 years 5 months ago
Neural networks for genetic epidemiology: past, present, and future
During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughpu...
Alison A. Motsinger-Reif, Marylyn D. Ritchie