2 citations · 3 across the 10 of their papers we have counts for
5 papers · 1 filter
Playing Non-Embedded Card-Based Games with Reinforcement Learning
Tianyang Wu, Lipeng Wan, Yuhang Wang +2
Significant progress has been made in AI for games, including board games, MOBA, and RTS games. However, complex agents are typically developed in an embedded manner, directly acce…
MInCo: Mitigating Information Conflicts in Distracted Visual Model-based Reinforcement Learning
Shiguang Sun, Hanbo Zhang, Zeyang Liu +4
Existing visual model-based reinforcement learning (MBRL) algorithms with observation reconstruction often suffer from information conflicts, making it difficult to learn compact r…
Enhancing Decision Transformer with Diffusion-Based Trajectory Branch Generation
Zhihong Liu, Long Qian, Zeyang Liu +3
Decision Transformer (DT) can learn effective policy from offline datasets by converting the offline reinforcement learning (RL) into a supervised sequence modeling task, where the…
Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning
Zeyang Liu, Lipeng Wan, Xinrui Yang +3
Effective exploration is crucial to discovering optimal strategies for multi-agent reinforcement learning (MARL) in complex coordination tasks. Existing methods mainly utilize intr…
Multi-agent Policy Optimization with Approximatively Synchronous Advantage Estimation
Lipeng Wan, Xuwei Song, Xuguang Lan +1
Cooperative multi-agent tasks require agents to deduce their own contributions with shared global rewards, known as the challenge of credit assignment. General methods for policy b…