Artificial Intelligence, Machine Learning, Data Science, Data, Reinforcement Learning.
minimax-optimal sample complexity without burn-in cost for tabular Markov decisionprocesses (MDPs). Concretely, consider a finite-horizon (resp. γ-discounted infinite-horizon) MDP with S states and horizon H(resp. effective horizon 11−γ), and suppose the distribution shift of data is reflected by