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Hierarchical Soft Actor-Critic: Adversarial Exploration via Mutual Information Optimization
Published 17 Jun 2019 in cs.LG, cs.AI, cs.IT, math.IT, and stat.ML | (1906.07122v1)
Abstract: We describe a novel extension of soft actor-critics for hierarchical Deep Q-Networks (HDQN) architectures using mutual information metric. The proposed extension provides a suitable framework for encouraging explorations in such hierarchical networks. A natural utilization of this framework is an adversarial setting, where meta-controller and controller play minimax over the mutual information objective but cooperate on maximizing expected rewards.
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