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Self-play

Training technique where an agent learns by playing against itself, generating its own experience data without requiring human opponents or labeled examples.

Wikidata

1 milestone

TD-Gammon Developed by Gerald Tesauro at IBM

In 1992, Gerald Tesauro at IBM Thomas J. Watson Research Center developed TD-Gammon, a backgammon program that trained itself through self-play using temporal-difference learning applied to a multilayer neural network, reaching a standard of play close to that of strong human experts.