13 citations · 13 across the 4 of their papers we have counts for
3 papers · 1 filter
Efficient Diffusion Planning with Temporal Diffusion
Jiaming Guo, Rui Zhang, Zerun Li +7
Diffusion planning is a promising method for learning high-performance policies from offline data. To avoid the impact of discrepancies between planning and reality on performance,…
Policy Constraint by Only Support Constraint for Offline Reinforcement Learning
Yunkai Gao, Jiaming Guo, Fan Wu +1
Offline reinforcement learning (RL) aims to optimize a policy by using pre-collected datasets, to maximize cumulative rewards. However, offline reinforcement learning suffers chall…
Automated Reinforcement Learning: An Overview
Reza Refaei Afshar, Joaquin Vanschoren, Uzay Kaymak +4
Reinforcement Learning and, recently, Deep Reinforcement Learning are popular methods for solving sequential decision-making problems modeled as Markov Decision Processes. RL model…