22 citations · 31 across the 3 of their papers we have counts for
3 papers · 1 filter
Active Model Estimation in Markov Decision Processes
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta +2
We study the problem of efficient exploration in order to learn an accurate model of an environment, modeled as a Markov decision process (MDP). Efficient exploration in this probl…
No-Regret Exploration in Goal-Oriented Reinforcement Learning
Jean Tarbouriech, Evrard Garcelon, Michal Valko +2
Many popular reinforcement learning problems (e.g., navigation in a maze, some Atari games, mountain car) are instances of the episodic setting under its stochastic shortest path (…
Active Exploration in Markov Decision Processes
Jean Tarbouriech, Alessandro Lazaric
We introduce the active exploration problem in Markov decision processes (MDPs). Each state of the MDP is characterized by a random value and the learner should gather samples to e…