no code implementations • 16 Dec 2019 • Dan Schmidt, Nick Moran, Jonathan S. Rosenfeld, Jonathan Rosenthal, Jonathan Yedidia
The AlphaZero algorithm for the learning of strategy games via self-play, which has produced superhuman ability in the games of Go, chess, and shogi, uses a quantitative reward function for game outcomes, requiring the users of the algorithm to explicitly balance different components of the reward against each other, such as the game winner and margin of victory.
no code implementations • 12 May 2015 • Charles Mathy, Nate Derbinsky, José Bento, Jonathan Rosenthal, Jonathan Yedidia
We describe a new instance-based learning algorithm called the Boundary Forest (BF) algorithm, that can be used for supervised and unsupervised learning.
