2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement Learning
Yangkun Chen, Kai Yang, Jian Tao +1
Recently, deep Multi-Agent Reinforcement Learning (MARL) has demonstrated its potential to tackle complex cooperative tasks, pushing the boundaries of AI in collaborative environme…
cs.LG2024★ 2 cited
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task Allocation
Aicheng Gong, Kai Yang, Jiafei Lyu +1
Task allocation is a key combinatorial optimization problem, crucial for modern applications such as multi-robot cooperation and resource scheduling. Decision makers must allocate…
cs.LG2024★ 1 cited
SEABO: A Simple Search-Based Method for Offline Imitation Learning
Jiafei Lyu, Xiaoteng Ma, Le Wan +3
Offline reinforcement learning (RL) has attracted much attention due to its ability in learning from static offline datasets and eliminating the need of interacting with the enviro…