13 citations · 52 across the 27 of their papers we have counts for
10 papers · 1 filter
PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning
Hangyu Mao, Rui Zhao, Ziyue Li +7
Designing better deep networks and better reinforcement learning (RL) algorithms are both important for deep RL. This work studies the former. Specifically, the Perception and Deci…
Adaptive parameter sharing for multi-agent reinforcement learning
Dapeng Li, Na Lou, Bin Zhang +2
Parameter sharing, as an important technique in multi-agent systems, can effectively solve the scalability issue in large-scale agent problems. However, the effectiveness of parame…
TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems
Yilun Kong, Jingqing Ruan, Yihong Chen +9
Large Language Models (LLMs) have demonstrated proficiency in addressing tasks that necessitate a combination of task planning and the usage of external tools that require a blend…
Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach
Bin Zhang, Hangyu Mao, Jingqing Ruan +9
The remarkable progress in Large Language Models (LLMs) opens up new avenues for addressing planning and decision-making problems in Multi-Agent Systems (MAS). However, as the numb…
TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage
Jingqing Ruan, Yihong Chen, Bin Zhang +8
With recent advancements in natural language processing, Large Language Models (LLMs) have emerged as powerful tools for various real-world applications. Despite their prowess, the…
Stackelberg Decision Transformer for Asynchronous Action Coordination in Multi-Agent Systems
Bin Zhang, Hangyu Mao, Lijuan Li +4
Asynchronous action coordination presents a pervasive challenge in Multi-Agent Systems (MAS), which can be represented as a Stackelberg game (SG). However, the scalability of exist…
From Explicit Communication to Tacit Cooperation:A Novel Paradigm for Cooperative MARL
Dapeng Li, Zhiwei Xu, Bin Zhang +1
Centralized training with decentralized execution (CTDE) is a widely-used learning paradigm that has achieved significant success in complex tasks. However, partial observability i…
SEA: A Spatially Explicit Architecture for Multi-Agent Reinforcement Learning
Dapeng Li, Zhiwei Xu, Bin Zhang +1
Spatial information is essential in various fields. How to explicitly model according to the spatial location of agents is also very important for the multi-agent problem, especial…
Inducing Stackelberg Equilibrium through Spatio-Temporal Sequential Decision-Making in Multi-Agent Reinforcement Learning
Bin Zhang, Lijuan Li, Zhiwei Xu +2
In multi-agent reinforcement learning (MARL), self-interested agents attempt to establish equilibrium and achieve coordination depending on game structure. However, existing MARL a…
Dual Self-Awareness Value Decomposition Framework without Individual Global Max for Cooperative Multi-Agent Reinforcement Learning
Zhiwei Xu, Bin Zhang, Dapeng Li +3
Value decomposition methods have gained popularity in the field of cooperative multi-agent reinforcement learning. However, almost all existing methods follow the principle of Indi…