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» Scalable Neural Networks for Board Games
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ICANN
2009
Springer
14 years 2 months ago
Scalable Neural Networks for Board Games
Learning to solve small instances of a problem should help in solving large instances. Unfortunately, most neural network architectures do not exhibit this form of scalability. Our...
Tom Schaul, Jürgen Schmidhuber
PPSN
2010
Springer
13 years 8 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
NIPS
1994
13 years 11 months ago
Learning to Play the Game of Chess
This paper presents NeuroChess, a program which learns to play chess from the final outcome of games. NeuroChess learns chess board evaluation functions, represented by artificial...
Sebastian Thrun
GECCO
2004
Springer
14 years 3 months ago
Evolving a Roving Eye for Go
Go remains a challenge for artificial intelligence. Currently, most machine learning methods tackle Go by playing on a specific fixed board size, usually smaller than the standa...
Kenneth O. Stanley, Risto Miikkulainen
ACG
2003
Springer
14 years 3 months ago
Evaluation in Go by a Neural Network using Soft Segmentation
In this article a neural network architecture is presented that is able to build a soft segmentation of a two-dimensional input. This network architecture is applied to position ev...
Markus Enzenberger