A New Machine-Learning Technique Applied to the Game of Checkers
dc.date.accessioned | 2004-10-04T14:08:38Z | |
dc.date.accessioned | 2018-11-24T10:11:00Z | |
dc.date.available | 2004-10-04T14:08:38Z | |
dc.date.available | 2018-11-24T10:11:00Z | |
dc.date.issued | 1966-03-01 | en_US |
dc.identifier.uri | http://hdl.handle.net/1721.1/5896 | |
dc.identifier.uri | http://repository.aust.edu.ng/xmlui/handle/1721.1/5896 | |
dc.description.abstract | This paper described a recent refinement of the machine--learning process employed by Samuel (1) in connection with his development of a checker playing program. Samuels checker player operates in much the same way a human player does; by looking ahead, and by making a qualitative judgment of the strength of the board positions it encounters. A machine learning process is applied to the development of an accurate procedure for making this strength evaluation of board positions. Before discussing my modifications to Samuels learning process, I should like to describe briefly Samuel's strength evaluation procedure, and the associated learning process. | en_US |
dc.format.extent | 7 p. | en_US |
dc.format.extent | 5529659 bytes | |
dc.format.extent | 362611 bytes | |
dc.language.iso | en_US | |
dc.title | A New Machine-Learning Technique Applied to the Game of Checkers | en_US |
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