2 papers
cs.LG2026
EMAN: Optimization-Driven Capacity Growth through Path Emergence in Multi-Task Learning
Chenlei Fang, Jingchen Li, Hongzong LI +5
Existing multi-task learning methods rely on hard sharing, multiple paths or experts, adaptive sharing, and dynamic expansion. However, their capacity changes are usually constrain…
cs.MA2022
A Decentralized Communication Framework based on Dual-Level Recurrence for Multi-Agent Reinforcement Learning
Jingchen Li, Haobin Shi, Kao-Shing Hwang
We propose a model enabling decentralized multiple agents to share their perception of environment in a fair and adaptive way. In our model, both the current message and historical…