15 citations · 16 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 15 cited
Computably Continuous Reinforcement-Learning Objectives are PAC-learnable
Cambridge Yang, Michael Littman, Michael Carbin
In reinforcement learning, the classic objectives of maximizing discounted and finite-horizon cumulative rewards are PAC-learnable: There are algorithms that learn a near-optimal p…
cs.LG2022★ 1 cited
Reinforcement Causal Structure Learning on Order Graph
Dezhi Yang, Guoxian Yu, Jun Wang +2
Learning directed acyclic graph (DAG) that describes the causality of observed data is a very challenging but important task. Due to the limited quantity and quality of observed da…