Journal article

Improved reinforcement learning with curriculum

J West, F Maire, C Browne, S Denman

Expert Systems with Applications | Elsevier | Published : 2020

Abstract

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 first concepts learned is how the game ends, i.e. the actions that lead to a terminal state (win, lose or draw). The advantage of learning end-games first is that once the actions leading to a terminal state are understood, it becomes possible to incrementally learn the consequences of actions that are further away from a terminal state – we call this an end-game-first curriculum. The state-of-the-art machine learning player for general board games, AlphaZero by Google DeepMind, does not employ a structured training c..

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