Year: 1996
Type: conference-paper
Abstract: We study the close connections between game theory, on-line prediction and boosting.After a brief review of game theory, we describe an algorithm for learning to play repeated games based on the on-line prediction methods of Littlestone and Warmuth.The analysis of this algorithm yields a simple proof of von Neumann's famous minmax theorem, as well as a provable method of approximately solving a game.We then show that the on-line prediction model is obtained by applying this gameplaying algorithm to an appropriate choice of game and that boosting is obtained by applying the same algorithm to the "dual" of this game.
Source: Conference on Learning Theory
Authors: Yoav Freund, Robert E. Schapire
Institution: AT&T (United States)
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W2097477220