Practical Issues in Temporal Difference Learning
Machine Learning
Temporal difference learning and TD-Gammon
Communications of the ACM
Programming backgammon using self-teaching neural nets
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Application of reinforcement learning to the game of Othello
Computers and Operations Research
Temporal difference learning applied to a high-performance game-playing program
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Algorithms for Reinforcement Learning
Algorithms for Reinforcement Learning
*-MINIMAX performance in backgammon
CG'04 Proceedings of the 4th international conference on Computers and Games
| Hi-index | 0.00 |
Backgammon is a board game that has been studied considerably by computer scientists. Apart from standard backgammon, several yet unexplored variants of the game exist, which use the same board, number of checkers, and dice but may have different rules for moving the checkers, starting positions and movement direction. This paper studies two popular variants in Greece and neighboring countries, named Fevga and Plakoto. Using reinforcement learning and Neural Network function approximation we train agents that learn a game position evaluation function for these games. We show that the resulting agents significantly outperform the open-source program Tavli3D.