Reinforcement learning framework for modeling spatial sequential decisions under uncertainty: (Extended abstract)

• Main Authors: LE, Truc Viet, LIU, Siyuan, LAU, Hoong Chuin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: reinforcement learning; budget constraint; stochastic utility; markov decision process; sequential decisions; trajectory prediction; Artificial Intelligence and Robotics; Computer Sciences; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3403; https://ink.library.smu.edu.sg/context/sis_research/article/4404/viewcontent/ReinforcementLearningRameworkSSD_AAMAS_2016.pdf
• Institution: Singapore Management University

We consider the problem of trajectory prediction, where a trajectory is an ordered sequence of location visits and corresponding timestamps. The problem arises when an agent makes sequential decisions to visit a set of spatial locations of interest. Each location bears a stochastic utility and the a...