13 citations · 30 across the 6 of their papers we have counts for
9 papers
Perceiving the World: Question-guided Reinforcement Learning for Text-based Games
Yunqiu Xu, Meng Fang, Ling Chen +3
Text-based games provide an interactive way to study natural language processing. While deep reinforcement learning has shown effectiveness in developing the game playing agent, th…
Rethinking Goal-conditioned Supervised Learning and Its Connection to Offline RL
Rui Yang, Yiming Lu, Wenzhe Li +6
Solving goal-conditioned tasks with sparse rewards using self-supervised learning is promising because of its simplicity and stability over current reinforcement learning (RL) algo…
Generalization in Text-based Games via Hierarchical Reinforcement Learning
Yunqiu Xu, Meng Fang, Ling Chen +2
Deep reinforcement learning provides a promising approach for text-based games in studying natural language communication between humans and artificial agents. However, the general…
Safe Exploration by Solving Early Terminated MDP
Hao Sun, Ziping Xu, Meng Fang +4
Safe exploration is crucial for the real-world application of reinforcement learning (RL). Previous works consider the safe exploration problem as Constrained Markov Decision Proce…
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…