research
∙
02/04/2022
Tsetlin Machine for Solving Contextual Bandit Problems
This paper introduces an interpretable contextual bandit algorithm using...
share
research
∙
10/17/2020
Approximate information state for approximate planning and reinforcement learning in partially observed systems
We propose a theoretical framework for approximate planning and learning...
research
∙
12/11/2019
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning
We study the problem of off-policy critic evaluation in several variants...
research
∙
12/11/2019