Titlebook: Artificial Intelligence XXXVI; 39th SGAI Internatio Max Bramer,Miltos Petridis Conference proceedings 2019 Springer Nature Switzerland AG 2

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https://doi.org/10.1007/978-3-030-59908-9re in the action space can improve sample efficiency during exploration. To show this we focus on concurrent action spaces where the RL agent selects multiple actions per timestep. Concurrent action spaces are challenging to learn in especially if the number of actions is large as this can lead to a

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