Research map / Reinforcement learning / Offline RL
On the Role of General Function Approximation in Offline Reinforcement Learning
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Theoretical study of offline RL with general function approximation that clarifies which function class assumptions are needed for different approximation targets.
Problem
Offline RL with general function approximation faces challenges because varying approximation targets and assumptions blur the meaning of function-class assumptions.
Approach
Formulates and clarifies the treatment of general function approximation in offline RL, separating approximation targets and their assumptions so that the real meaning of each assumption is explicit.
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