Neighborhood cooperative multiagent reinforcement learning for adaptive traffic signal control in epidemic regions

• Main Authors: ZHANG, Chengwei, TIAN, Yu, ZHANG, Zhibin, XUE, Wanli, XIE, Xiaofei, YANG, Tianpei, GE, Xin, CHEN, Rong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Correlation; Games; Training; Markov processes; Epidemics; Roads; Electronic mail; Multi-agent learning; cooperative Markov game; independent reinforcement learning; adaptive traffic signal control; Artificial Intelligence and Robotics; Theory and Algorithms; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/9852; https://ink.library.smu.edu.sg/context/sis_research/article/10852/viewcontent/T_ITS_NeighbourhoodCooperativeMultiagent_av.pdf
• Institution: Singapore Management University

Nowadays, multiagent reinforcement learning (MARL) have shared significant advances in the adaptive traffic signal control (ATSC) problems. For most of the researches, agents are all isomorphic, which disregards the situation in which isomerous intersections cooperative together in a real ATSC scena...