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Solving Atari Games Using Fractals And Entropy
July 03, 2018 Β· Declared Dead Β· π arXiv.org
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Authors
Sergio Hernandez Cerezo, Guillem Duran Ballester, Spiros Baxevanakis
arXiv ID
1807.01081
Category
cs.AI: Artificial Intelligence
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
In this paper, we introduce a novel MCTS based approach that is derived from the laws of the thermodynamics. The algorithm coined Fractal Monte Carlo (FMC), allows us to create an agent that takes intelligent actions in both continuous and discrete environments while providing control over every aspect of the agent behavior. Results show that FMC is several orders of magnitude more efficient than similar techniques, such as MCTS, in the Atari games tested.
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