Towards explaining sequences of actions in multi-agent deep reinforcement learning models

• Main Authors: KHAING, Phyo Wai, GENG, Minghong, SUBAGDJA, Budhitama, PATERIA, Shubham, TAN, Ah-hwee
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Multi Agent Deep Reinforcement Learning; Explainable Artificial Intelligence; Explainable Deep Reinforcement Learning; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/8076; https://ink.library.smu.edu.sg/context/sis_research/article/9079/viewcontent/p2325.pdf
• Institution: Singapore Management University

Although Multi-agent Deep Reinforcement Learning (MADRL) has shown promising results in solving complex real-world problems, the applicability and reliability of MADRL models are often limited by a lack of understanding of their inner workings for explaining the decisions made. To address this issue...