COIN Framework Overview (IMAGE)
Caption
The overall COIN framework, which follows the CTDE paradigm. During training, an individual critic learns individual Q-values to guide the ego vehicle’s navigation policy, while a centralized critic learns global Q-values to facilitate collaborative policy learning. These two critics work together to achieve joint policy optimization. During execution, the actor learns an end-to-end policy based only on local observations. The right side illustrates the roles of the individual critic and centralized critic. Notably, we design a dual-level interaction-aware centralized critic with a counterfactual baseline to improve credit assignment and promote better agent cooperation.
Credit
MARMot Lab, National University of Singapore
Usage Restrictions
Credit must be given to the creator.
License
CC BY