Abstract: A number of recent approaches to policy learning in 2D game domains have been successful going directly from raw input images to actions. However when employed in complex 3D environments, they typically suffer from challenges related to partial observability, combinatorial exploration spaces, path planning, and a scarcity of rewarding scenarios.
Reinforcement Learning ile Doom oynamak: [1612.00380] Playing Doom with SLAM- Augmented Deep Reinforcement Learning
arxiv.org
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