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Mini-Batch Risk-Averse Deep Q-Learning: A Robot Navigation Case Study
We study the control of Markov decision processes in which the quality of a policy is evaluated by a dynamic, time-consistent Markov risk measure rather than by an expected discounted cost. The main obstacle to combining such measures with reinforcement learning is that a transition risk mapping dep
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