6 papers
Understanding and Stabilizing Deep Q-Learning via Controlled Bootstrapping and Regulated Value Dynamics
Bozhou Chen, Yongyi Wang, Hanyu Liu +2
Deep Q-learning (DQL) has achieved remarkable empirical success in reinforcement learning, yet its training process remains notoriously unstable. Existing studies often attribute i…
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…
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…
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…