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» Evolving Neural Networks to Play Go
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GECCO
2007
Springer
201views Optimization» more  GECCO 2007»
13 years 11 months ago
Evolving explicit opponent models in game playing
Opponent models are necessary in games where the game state is only partially known to the player, since the player must infer the state of the game based on the opponent’s acti...
Alan J. Lockett, Charles L. Chen, Risto Miikkulain...
PPSN
2010
Springer
13 years 4 months ago
Indirect Encoding of Neural Networks for Scalable Go
Abstract. The game of Go has attracted much attention from the artificial intelligence community. A key feature of Go is that humans begin to learn on a small board, and then incr...
Jason Gauci, Kenneth O. Stanley
CEC
2005
IEEE
13 years 11 months ago
Coevolution of neural Go players in a cultural environment
Abstract- We present experiments (co)evolving Go players based on artificial neural networks (ANNs) for a 5x5 board. ANN structure and weights are encoded in multi–chromosomal g...
Helmut A. Mayer, Peter Maier
AAAI
1994
13 years 7 months ago
Evolving Neural Networks to Focus Minimax Search
Neural networks were evolved through genetic algorithms to focus minimax search in the game of Othello. At each level of the search tree, the focus networks decide which moves are...
David E. Moriarty, Risto Miikkulainen
CIBCB
2008
IEEE
14 years 3 days ago
Classification of mouse fRNA genes using evolved neural networks
Functional RNAs (fRNAs) play a key role in gene regulation, at both the transcriptional and translational levels. Identification of fRNA genes can be difficult, given that some cla...
Mars Cheung, Gary B. Fogel