Reinforcement Learning in Non-Stationary Environments
When the agent's state is an image, the explanation of its decision can be done with saliency maps of pixels [10] or objects [13], but also in a counterfactual.
AIRS: Explanation for Deep Reinforcement Learning based Security ...The objective is to stimulate interaction and collaboration between children while teaching the robot, and also provide them tangible examples ... Predicate-based explanation of a Reinforcement Learning agent via ...There are number of ways to linearly parameterize an MDP such that it permits for efficient reinforcement learning. (both statistically and computationally) ... rltheorybook_AJKS.pdfApplying robust RL to power system ap- plications is an important future direction to deal with parametric uncertainties, data errors, and ...
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