Bootstrapping simulation-based algorithms with a suboptimal policy

• Main Authors: Nguyen T., Silander T., Lee W., Tze-Yun LEONG
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: markov decision process; sparse sampling; forward sparse sampling; uct; heuristic; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/3000; https://ink.library.smu.edu.sg/context/sis_research/article/4000/viewcontent/7934_37003_2_PB.pdf
• Institution: Singapore Management University

Finding optimal policies for Markov Decision Processes with large state spaces is in general intractable. Nonetheless, simulation-based algorithms inspired by Sparse Sampling (SS) such as Upper Confidence Bound applied in Trees (UCT) and Forward Search Sparse Sampling (FSSS) have been shown to perfo...