Systematic Analyses of Reinforcement Learning Controllers in Signalized Urban Corridors

Systematic Analyses of Reinforcement Learning Controllers in Signalized Urban Corridors explores This paper explores the theoretical capacity regions of different reinforcement learning controllers for urban traffic networks, comparing them to a classical baseline.. Commercial viability score: 3/10 in Reinforcement Learning for Traffic Control.