535515 Spring 2023 - Reinforcement Learning (強化學習原理)

  • Instructor: Ping-Chun Hsieh

  • Email: pinghsieh [AT] nycu [DOT] edu [DOT] tw

  • Lectures:

    • Tuesdays 3:30pm-4:20pm @ EC115

    • Fridays 10:10am-12:00noon @ EC115

    • Note: The first lecture on 2/14 (Tue.) will be delivered via Webex: Webex Link

  • Office Hours: 4:30pm-5pm on Tuesdays or by appointment

  • References:

    • [SB] Richard Sutton and Andrew Barto, Reinforcement Learning: An Introduction, 2nd edition, 2019

    • [AJK] Alekh Agarwal, Nan Jiang Sham M. Kakade, Reinforcement Learning: Theory and Algorithms, 2020 (https://rltheorybook.github.io/rlmonographAJK.pdf)

    • [BCN] Léon Bottou, Frank E. Curtis, and Jorge Nocedal, Optimization Methods for Large-Scale Machine Learning (https://arxiv.org/abs/1606.04838)

    • [NW] Jorge Nocedal and Stephen Wright, Numerical optimization, 2006

    • [LS] Tor Lattimore and Csaba Szepesvari, Bandit Algorithms, 2019 (https://tor-lattimore.com/downloads/book/book.pdf)

  • Grading

    • Assignments: 35%

    • Theory Project: 30%

    • Team Implementation Project: 35% (Report: 20%, Presentation: 15%)

  • Lecture Schedule: