Advances in neural information processing systems 2
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
TD-Gammon, a self-teaching backgammon program, achieves master-level play
Neural Computation
Temporal difference learning and TD-Gammon
Communications of the ACM
Constructive Function Approximation TITLE2:
Constructive Function Approximation TITLE2:
Some studies in machine learning using the game of checkers
IBM Journal of Research and Development
Game playing (invited talk): the next moves
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
IEEE Intelligent Systems
Learning from Perfection. A Data Mining Approach to Evaluation Function Learning in Awari
CG '00 Revised Papers from the Second International Conference on Computers and Games
Analytical features: a knowledge-based approach to audio feature generation
EURASIP Journal on Audio, Speech, and Music Processing
Automatic construction of static evaluation functions for computer game players
DS'06 Proceedings of the 9th international conference on Discovery Science
Automated discovery of search-extension features
ACG'09 Proceedings of the 12th international conference on Advances in Computer Games
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This paper discusses a practical framework for the semi-automatic construction of evaluation-functions for games. Based on a structured evaluation function representation, a procedure for exploring the feature space is presented that is able to discover new features in a computationally feasible way. Besides the theoretical aspects, related practical issues such as the generation of training positions, feature selection, and weight fitting in large linear systems are discussed. Finally, we present experimental results for Othello, which demonstrate the potential of the described approach.