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Classical Planning Algorithms on the Atari Video Games

Lipovetzky, Nir; Ramirez, Miguel; Geffner, Hector


The Atari 2600 games supported in the Arcade Learning Environment [Bellemare et al., 2013] all feature a known initial (RAM) state and actions that have deterministic effects. Classical planners, however, cannot be used off-the-shelf as there is no compact PDDL-model of the games, and action effects and goals are not known a priori. Indeed, there are no explicit goals, and the planner must select actions on-line while interacting with a simulator that returns successor states and rewards. None...[Show more]

CollectionsANU Research Publications
Date published: 2015
Type: Conference paper
Source: Classical Planning Algorithms on the Atari Video Games


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