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» Scalable Neural Networks for Board Games
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ICANN
2009
Springer
13 years 9 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 3 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 6 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
13 years 10 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
13 years 10 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