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Investigating Reinforcement Learning Agents for Continuous State Space Environments

08/08/2017

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by David Von Dollen, et al.

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Given an environment with continuous state spaces and discrete actions, we investigate using a Double Deep Q-learning Reinforcement Agent to find optimal policies using the LunarLander-v2 OpenAI gym environment.

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