151 citations · 254 across the 10 of their papers we have counts for
10 papers
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
Rui Yang, Han Zhong, Jiawei Xu +4
Offline reinforcement learning (RL) presents a promising approach for learning reinforced policies from offline datasets without the need for costly or unsafe interactions with the…
Principled Exploration via Optimistic Bootstrapping and Backward Induction
Chenjia Bai, Lingxiao Wang, Lei Han +4
One principled approach for provably efficient exploration is incorporating the upper confidence bound (UCB) into the value function as a bonus. However, UCB is specified to deal w…
TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning
Peng Sun, Jiechao Xiong, Lei Han +5
Competitive Self-Play (CSP) based Multi-Agent Reinforcement Learning (MARL) has shown phenomenal breakthroughs recently. Strong AIs are achieved for several benchmarks, including D…
TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full Game
Lei Han, Jiechao Xiong, Peng Sun +8
StarCraft, one of the most difficult esport games with long-standing history of professional tournaments, has attracted generations of players and fans, and also, intense attention…
Arena: a toolkit for Multi-Agent Reinforcement Learning
Qing Wang, Jiechao Xiong, Lei Han +5
We introduce Arena, a toolkit for multi-agent reinforcement learning (MARL) research. In MARL, it usually requires customizing observations, rewards and actions for each agent, cha…
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space
Jiechao Xiong, Qing Wang, Zhuoran Yang +7
Most existing deep reinforcement learning (DRL) frameworks consider either discrete action space or continuous action space solely. Motivated by applications in computer games, we…