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For questions related to reinforcement learning, i.e. a machine learning technique where we imagine an agent that interacts with an environment (composed of states) in time steps by taking actions and receiving rewards (or reinforcements), then, based on these interactions, the agent tries to find a policy (i.e. a behavioural strategy) that maximizes the cumulative reward (in the long run), so the goal of the agent is to maximize the reward.

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I am looking for a gentle introduction (videos, lecture notes, tutorials, books) on reinforcement learning (MDPs) involving continuous states (or very large cardinality of state space). In particular, …
asked Jul 14 '21 by cgo