10 citations · 18 across the 10 of their papers we have counts for
3 papers · 1 filter
Manipulating the Distributions of Experience used for Self-Play Learning in Expert Iteration
Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson +1
Expert Iteration (ExIt) is an effective framework for learning game-playing policies from self-play. ExIt involves training a policy to mimic the search behaviour of a tree search…
Learning Policies from Self-Play with Policy Gradients and MCTS Value Estimates
Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson +1
In recent years, state-of-the-art game-playing agents often involve policies that are trained in self-playing processes where Monte Carlo tree search (MCTS) algorithms and trained…
Improved Reinforcement Learning with Curriculum
Joseph West, Frederic Maire, Cameron Browne +1
Humans tend to learn complex abstract concepts faster if examples are presented in a structured manner. For instance, when learning how to play a board game, usually one of the fir…