Machine Learning
Some Studies in Machine Learning Using the Game of Checkers, II - Recent Progress
A new signature table technique is described together with an improved book learning procedure which is thought to be much superior to the linear polynomial method described earlier. Full use is made of the so called âalpha-betaâ pruning and several forms of forward pruning to restrict the spread of the move tree and to permit the program to look ahead to a much greater depth than it other- wise could do. While still unable to outplay checker masters, the programâs playing ability has been greatly improved.See also:IEEE XploreAnnual Review in Automatic Programming, Volume 6, Part 1, 1969, Pages 1–36Some Studies in Machine Learning Using the Game of CheckersIBM J of Research and Development ll, No.6, 1967,601
Game-playing and game-learning automata
In Fox, L. (Ed.), Advances in Programming and Non-Numerical Computation, pp. 183â200. Pergamon.
Statistical inference for probabilistic functions of finite state Markov chains
Annals of Mathematical Statistics, 41.
Optimal control of partially observable Markov systems
J. Franklin Institute, 280 (5), 367-86
Optimal control of Markov decision processes with incomplete state estimation
J. Math. Anal. Applic., 10, 174–205.
Maximum likelihood estimates of linear dynamic systems
Rauch, H. E., Tung, F., Striebel, C. T.
AIAA Journal, 3 (8), 1445-1450.
Learning Machines: Foundations of Trainable Pattern-Classifying Systems
Republished as The Mathematical Foundations of Learning Machines, San Francisco: Morgan Kaufmann Publishers, 1990McGraw-Hill. Republished in 1990.
Theoretical foundations of the potential function method in pattern recognition learning
Aizerman, M. | Braverman, E. | Rozonoer, L.
Automation and Remote Control, 25, 821–837
A formal theory of inductive inference
Information and Control, 7, 1â22, 224â254.