We study the autonomous exploration (AX) problem proposed by Lim Aue...
We study the sample complexity of learning an ϵ-optimal policy in
the St...
We consider regret minimization for Adversarial Markov Decision Processe...
We initiate the study of dynamic regret minimization for goal-oriented
r...
Reinforcement learning constantly deals with hard integrals, for example...
Policy optimization is among the most popular and successful reinforceme...
We study regret minimization for infinite-horizon average-reward Markov
...
We introduce two new no-regret algorithms for the stochastic shortest pa...
We introduce a generic template for developing regret minimization algor...
We consider the problem of online reinforcement learning for the Stochas...
We make significant progress toward the stochastic shortest path problem...
We resolve the long-standing "impossible tuning" issue for the classic e...
We study the stochastic shortest path problem with adversarial costs and...
The ability to transfer in reinforcement learning is key towards buildin...