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cs.LG2021
The Role of Lookahead and Approximate Policy Evaluation in Reinforcement Learning with Linear Value Function Approximation
Anna Winnicki, Joseph Lubars, Michael Livesay +1
Function approximation is widely used in reinforcement learning to handle the computational difficulties associated with very large state spaces. However, function approximation in…
cs.LG2021★ 1 cited
Optimistic Policy Iteration for MDPs with Acyclic Transient State Structure
Joseph Lubars, Anna Winnicki, Michael Livesay +1
We consider Markov Decision Processes (MDPs) in which every stationary policy induces the same graph structure for the underlying Markov chain and further, the graph has the follow…