Deep Apprenticeship Learning for Playing Video Games

Miroslav Bogdanovic, Dejan Markovikj, Misha Denil, Nando de Freitas

Abstract: Recently it has been shown that deep neural networks can learn to play Atari games by directly observing raw pixels of the playing area. We show how apprenticeship learning can be applied in this setting so that an agent can learn to perform a task (i.e. play a game) by observing the expert, without any explicitly provided knowledge of the game’s internal state or objectives.