Centralizing State-Values in Dueling Networks for Multi-Robot Reinforcement Learning Mapless Navigation
Enrico Marchesini,Alessandro Farinelli,Enrico Marchesini,Alessandro Farinelli
We study the problem of multi-robot mapless navigation in the popular Centralized Training and Decentralized Execution (CTDE) paradigm. This problem is challenging when each robot considers its path without explicitly sharing observations with other robots and can lead to non-stationary issues in Deep Reinforcement Learning (DRL). The typical CTDE algorithm factorizes the joint action-value functi...
