1 citations · 1 across the 8 of their papers we have counts for
9 papers
Beyond Autoregressive RTG: Conditioning via Injection Outside Sequential Modeling in Decision Transformer
Yongyi Wang, Hanyu Liu, Lingfeng Li +6
Decision Transformer (DT) formulates offline reinforcement learning as autoregressive sequence modeling, achieving promising results by predicting actions from a sequence of Return…
System Design for Maintaining Internal State Consistency in Long-Horizon Robotic Tabletop Games
Guangyu Zhao, Ceyao Zhang, Chengdong Ma +16
Long-horizon tabletop games pose a distinct systems challenge for robotics: small perceptual or execution errors can invalidate accumulated task state, propagate across decision-ma…
Pareto-guided Pipeline for Distilling Featherweight AI Agents in Mobile MOBA Games
Xionghui Yang, Bozhou Chen, Yunlong Lu +8
Recent advances in game AI have demonstrated the feasibility of training agents that surpass top-tier human professionals in complex environments such as Honor of Kings (HoK), a le…
BotzoneBench: Scalable LLM Evaluation via Graded AI Anchors
Lingfeng Li, Yunlong Lu, Yuefei Zhang +7
Large Language Models (LLMs) are increasingly deployed in interactive environments requiring strategic decision-making, yet systematic evaluation of these capabilities remains chal…
Decoupling Return-to-Go for Efficient Decision Transformer
Yongyi Wang, Hanyu Liu, Lingfeng Li +5
The Decision Transformer (DT) has established a powerful sequence modeling approach to offline reinforcement learning. It conditions its action predictions on Return-to-Go (RTG), u…
Adapting Rules of Official International Mahjong for Online Players
Chucai Wang, Lingfeng Li, Yunlong Lu +1
As one of the worldwide spread traditional game, Official International Mahjong can be played and promoted online through remote devices instead of requiring face-to-face interacti…
Synthetic POMDPs to Challenge Memory-Augmented RL: Memory Demand Structure Modeling
Yongyi Wang, Lingfeng Li, Bozhou Chen +5
Recent benchmarks for memory-augmented reinforcement learning (RL) have introduced partially observable Markov decision process (POMDP) environments in which agents must use histor…
Policy Improvement with Style-Specific Demonstrations
Lingfeng Li, Yunlong Lu, Yongyi Wang +1
Proficient game agents with diverse play styles enrich the gaming experience and enhance the replay value of games. However, recent advancements in game AI based on reinforcement l…
Mxplainer: Explain and Learn Insights by Imitating Mahjong Agents
Lingfeng Li, Yunlong Lu, Yongyi Wang +2
People need to internalize the skills of AI agents to improve their own capabilities. Our paper focuses on Mahjong, a multiplayer game involving imperfect information and requiring…