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Towards Blackwell Optimality: Bellman Optimality Is All You Can Get
Victor Boone, Adrienne Tuynman
Although average gain optimality is a commonly adopted performance measure in Markov Decision Processes (MDPs), it is often too asymptotic. Further incorporating measures of immedi…
The Batch Complexity of Bandit Pure Exploration
Adrienne Tuynman, Rémy Degenne
In a fixed-confidence pure exploration problem in stochastic multi-armed bandits, an algorithm iteratively samples arms and should stop as early as possible and return the correct…
Finding good policies in average-reward Markov Decision Processes without prior knowledge
Adrienne Tuynman, Rémy Degenne, Emilie Kaufmann
We revisit the identification of an -optimal policy in average-reward Markov Decision Processes (MDP). In such MDPs, two measures of complexity have appeared in the li…
Transfer in Reinforcement Learning via Regret Bounds for Learning Agents
Adrienne Tuynman, Ronald Ortner
We present an approach for the quantification of the usefulness of transfer in reinforcement learning via regret bounds for a multi-agent setting. Considering a number of …