7 papers
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…
From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary
Qirui Zheng, Xingbo Wang, Keyuan Cheng +5
The advent of artificial intelligence has propelled AI-Generated Game Commentary (AI-GGC) into a rapidly expanding research area, offering advantages such as scalable availability…
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…
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…
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…