103 citations · 470 across the 31 of their papers we have counts for
10 papers · 1 filter
Hierarchical Task Network Planning for Facilitating Cooperative Multi-Agent Reinforcement Learning
Xuechen Mu, Hankz Hankui Zhuo, Chen Chen +3
Exploring sparse reward multi-agent reinforcement learning (MARL) environments with traps in a collaborative manner is a complex task. Agents typically fail to reach the goal state…
Introduction to The Dynamic Pickup and Delivery Problem Benchmark -- ICAPS 2021 Competition
Jianye Hao, Jiawen Lu, Xijun Li +4
The Dynamic Pickup and Delivery Problem (DPDP) is an essential problem within the logistics domain. So far, research on this problem has mainly focused on using artificial data whi…
Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
Tianze Zhou, Fubiao Zhang, Kun Shao +10
Extending transfer learning to cooperative multi-agent reinforcement learning (MARL) has recently received much attention. In contrast to the single-agent setting, the coordination…
Learning Symbolic Rules for Interpretable Deep Reinforcement Learning
Zhihao Ma, Yuzheng Zhuang, Paul Weng +4
Recent progress in deep reinforcement learning (DRL) can be largely attributed to the use of neural networks. However, this black-box approach fails to explain the learned policy i…
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning
Hangyu Mao, Wulong Liu, Jianye Hao +5
Social psychology and real experiences show that cognitive consistency plays an important role to keep human society in order: if people have a more consistent cognition about thei…
Multi-Agent Game Abstraction via Graph Attention Neural Network
Yong Liu, Weixun Wang, Yujing Hu +3
In large-scale multi-agent systems, the large number of agents and complex game relationship cause great difficulty for policy learning. Therefore, simplifying the learning process…