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Actively Learning Reinforcement Learning: A Stochastic Optimal Control Approach

By Mohammad Ramadan and others
In this paper we propose a framework towards achieving two intertwined objectives: (i) equipping reinforcement learning with active exploration and deliberate information gathering, such that it regulates state and parameter uncertainties resulting from modeling mismatches and noisy sensory; and (ii) overcoming the huge computational cost of stochastic optimal control. We... Show more
February 26, 2024
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Actively Learning Reinforcement Learning: A Stochastic Optimal Control Approach
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