Unsupervised training sequence design: Efficient and generalizable agent training

• Main Authors: LI, Wenjun, VARAKANTHAM, Pradeep
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/9362; https://ink.library.smu.edu.sg/context/sis_research/article/10362/viewcontent/29268_Article_Text_33322_1_2_20240324_pvoa.pdf
• Institution: Singapore Management University

To train generalizable Reinforcement Learning (RL) agents, researchers recently proposed the Unsupervised Environment Design (UED) framework, in which a teacher agent creates a very large number of training environments and a student agent trains on the experiences in these environments to be robust...