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Sample Complexity of Multi-task Reinforcement Learning
Emma Brunskill, Lihong Li
Transferring knowledge across a sequence of reinforcement-learning tasks is challenging, and has a number of important applications. Though there is encouraging empirical evidence…
Sequential Transfer in Multi-armed Bandit with Finite Set of Models
Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
Learning from prior tasks and transferring that experience to improve future performance is critical for building lifelong learning agents. Although results in supervised and reinf…
Regret Bounds for Reinforcement Learning with Policy Advice
Mohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill
In some reinforcement learning problems an agent may be provided with a set of input policies, perhaps learned from prior experience or provided by advisors. We present a reinforce…