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Memory-State Critic for Asymmetric Actor-Critic with Application to Vision-Based Pursuit-Evasion

Louette, Arthur et al.
arXiv (All) · Papers
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machine-learning
In partially observable Markov decision processes, the optimal policy generally depends on the history of observations and past actions. Asymmetric actor-critic methods have become popular to learn such policies when additional information, such as the true state of the environment, is available dur
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