7 papers · 1 filter
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…
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…
ShuttleEnv: An Interactive Data-Driven RL Environment for Badminton Strategy Modeling
Ang Li, Xinyang Gong, Bozhou Chen +5
We present ShuttleEnv, an interactive and data-driven simulation environment for badminton, designed to support reinforcement learning and strategic behavior analysis in fast-paced…
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…
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…