Events Calendar

Seminar Series: Reinforcement Learning and Markov Chain Computations

Prof. Vivek Borkar, Tata Institute of Fundamental Research (TIFR), Mumbai, India This two part series shall cover an introduction to reinforcement learning and stochastic approximations, and its application to Markov Chain computations.Part I (Tuesday, Oct. 6) shall highlight the main strands in the reinforcement learning based approaches to approximate dynamic programming for Markov decision processes. In particular, connections to numerical methods for MDPs and convergence issues will be discussed.Speaker Bio:
Vivek Borkar is a Professor in the School of Technology and Computer Science at the Tata Institute of Fundamental Research (TIFR), Mumbai where he has been for the last decade.
He was formerly Dean of the same school. Prior to TIFR, he was a Professor in the Computer Science and Automation department of the Indian Institute of Science, Bangalore. He received his Ph.D. from University of California, Berkeley in EECS in 1979. He is well-known for his work in many areas including stochastic processes, mathematical control, game theory and learning. He is the author of several books including a recent book on Stochastic approximations: A Dynamical Systems Viewpoint.Host: Prof. Rahul Jain, 213-740-2246, rahul.jain@usc.edu. If you would like to meet the speaker during his weeklong visit from October 5-9, please contact the host.

Location: Hedco Pertroleum and Chemical Engineering Building (HED) - 116

Audiences: Everyone Is Invited

Contact: Annie Yu