research
∙
11/23/2021
Adaptive Multi-Goal Exploration
We introduce a generic strategy for provably efficient multi-goal explor...
share
research
∙
10/27/2021
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching
Learning meaningful behaviors in the absence of reward is a difficult pr...
research
∙
04/22/2021
Stochastic Shortest Path: Minimax, Parameter-Free and Towards Horizon-Free Regret
We study the problem of learning in the stochastic shortest path (SSP) s...
research
∙
12/29/2020
Improved Sample Complexity for Incremental Autonomous Exploration in MDPs
We investigate the exploration of an unknown environment when no reward ...
research
∙
07/13/2020
A Provably Efficient Sample Collection Strategy for Reinforcement Learning
A common assumption in reinforcement learning (RL) is to have access to ...
research
∙
03/06/2020
Active Model Estimation in Markov Decision Processes
We study the problem of efficient exploration in order to learn an accur...
research
∙
12/07/2019
No-Regret Exploration in Goal-Oriented Reinforcement Learning
Many popular reinforcement learning problems (e.g., navigation in a maze...
research
∙
02/28/2019