Samuel’s Checkers Player
Samuel’s Checkers Player is the first machine learning system that received public recognition. It pioneered many important ideas in game playing and machine learning. The two main papers describing his research (Samuel, 1959, 1967) became landmark papers in Artificial Intelligence. In one game, the resulting program was able to beat one of America’s best players of the time.
Description of the Learning System
Samuel’s checkers player featured a wide variety of learning techniques. First, his checkers player remembered positions that it frequently encountered during play. This simple form of rote learning allowed it to save time, and to search deeper in subsequent games whenever a stored position was encountered on the board or in some line of calculation. Next, it featured the first successful application of what is now known as Reinforcement Learning for tuning the weights of its evaluation function. The program trained itself by pl ...
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- Samuel’s Checkers Player
- Reference Work Title
- Encyclopedia of Machine Learning
- p 881
- Print ISBN
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- Springer US
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- Springer Science+Business Media, LLC
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