Neurogammon 1.0 is a complete backgammon program which uses multi-layer neural networks to make move decisions and doubling decisions. The networks were trained by back-propagation on large expert data sets. Neu-rogammon appears to play backgammon at a substantially higher level than conventional programs. At the recently held First Computer Olympiad in London, Neurogammon won the backgammon competition with a perfect record of 5 wins and no losses, thereby becoming the first learning program ever to win any tournament. 1
Deep neural networks have been successfully applied in learning the board games Go, chess, and shogi...
The advancement of computing technology has allowed machines to defeat even the best human practitio...
This article defines the challenge of training neural-networks on specific chess endgames and benchm...
Diploma thesis Implementation of Backgammon player with neural network describes implementation of h...
AbstractTD-Gammon is a neural network that is able to teach itself to play backgammon solely by play...
Part 3: Artificial Neural NetworksInternational audienceRecently, a backgammon bot named Palamedes w...
TD-Gammon is a neural network that is able to teach itself to play backgammon solely by playing agai...
Go is a difficult game for computers to master, and the best go programs are still weaker than the a...
An agent controlled by a single developmental neuron is trained to play arcade game. Genetic program...
Project (M.S., Computer Science) -- California State University, Sacramento, 2013.Games are an inter...
An experiment was conducted where neural networks compete for survival in an evolving population bas...
NeuroDraughts is a draughts playing program which follows the approach of both NeuroGammon (G.Tesaur...
The best current computer Go programs are hand crafted expert sys-tems. They are using conventional ...
We have designed a backgammon program to play intelligent games. It can make good decisions of the m...
We describe a class of connectionist networks that have learned to play back-gammon at an intermedia...
Deep neural networks have been successfully applied in learning the board games Go, chess, and shogi...
The advancement of computing technology has allowed machines to defeat even the best human practitio...
This article defines the challenge of training neural-networks on specific chess endgames and benchm...
Diploma thesis Implementation of Backgammon player with neural network describes implementation of h...
AbstractTD-Gammon is a neural network that is able to teach itself to play backgammon solely by play...
Part 3: Artificial Neural NetworksInternational audienceRecently, a backgammon bot named Palamedes w...
TD-Gammon is a neural network that is able to teach itself to play backgammon solely by playing agai...
Go is a difficult game for computers to master, and the best go programs are still weaker than the a...
An agent controlled by a single developmental neuron is trained to play arcade game. Genetic program...
Project (M.S., Computer Science) -- California State University, Sacramento, 2013.Games are an inter...
An experiment was conducted where neural networks compete for survival in an evolving population bas...
NeuroDraughts is a draughts playing program which follows the approach of both NeuroGammon (G.Tesaur...
The best current computer Go programs are hand crafted expert sys-tems. They are using conventional ...
We have designed a backgammon program to play intelligent games. It can make good decisions of the m...
We describe a class of connectionist networks that have learned to play back-gammon at an intermedia...
Deep neural networks have been successfully applied in learning the board games Go, chess, and shogi...
The advancement of computing technology has allowed machines to defeat even the best human practitio...
This article defines the challenge of training neural-networks on specific chess endgames and benchm...