Abstract:
Deep Reinforcement Learning (DRL) is a promising data-driven approach for traffic signal control, especially because DRL can learn to adapt to varying traffic demands. For that, DRL agents maximize a scalar reward by interacting with an environment. However, one needs to formulate a suitable reward, aligning agent behavior and user objectives, which is an open research problem. We investigate this problem in the context of traffic signal control with the objective of minimizing CO2 emissio… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.