Multi-agent collaborative exploration through graph-based deep reinforcement learning

• Main Authors: LUO, Tianze, SUBAGDJA, Budhitama, TAN, Ah-hwee, TAN, Ah-Hwee
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Graph convolutional networks; Multi-agent map exploration; Multi-robot system; Reinforcement learning; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/6173; https://ink.library.smu.edu.sg/context/sis_research/article/7176/viewcontent/Full_27_PID6151059.pdf
• Institution: Singapore Management University

Autonomous exploration by a single or multiple agents in an unknown environment leads to various applications in automation, such as cleaning, search and rescue, etc. Traditional methods normally take frontier locations and segmented regions of the environment into account to efficiently allocate ta...