Sample-efficient iterative lower bound optimization of deep reactive policies for planning in continuous MDPs

• Main Authors: LOW, Siow Meng, KUMAR, Akshat, SANNER, Scott
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/sis_research/7724; https://ink.library.smu.edu.sg/context/sis_research/article/8727/viewcontent/21220_Article_Text_25233_1_2_20220628.pdf
• Institution: Singapore Management University

Recent advances in deep learning have enabled optimization of deep reactive policies (DRPs) for continuous MDP planning by encoding a parametric policy as a deep neural network and exploiting automatic differentiation in an end-toend model-based gradient descent framework. This approach has proven e...