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Séminaire informel de théorie des systèmes (ISS)

Reinforcement Learning for Non-Markovian Environments


13 jan. 2023   11h30 — 12h30

Vivek Borkar Département de génie électrique, Indian Institute of Technology Bombay, Inde

Vivek Borkar

Présentation sur YouTube

This talk will discuss some of what I feel to be key issues in dealing with reinforcement learning in non-Markovian environments, drawing parallels with some classical ideas in stochastic control. This will be used to motivate a particular objective, viz., approximation of certain conditional laws, which is very much in the tradition of control of POMDPs using belief states.

Biography: Vivek Borkar is currently an emeritus faculty at the Indian Institute of Technology Bombay, Mumbai. He studied electrical engineering at IIT Bombay and subsequently did his M.S. and Ph.D. in resp. Case Western Reserve Uni. and Uni. of California at Berkeley. His interests are in stochastic control and optimization, covering theory, algorithms and applications.

Peter E. Caines responsable
Aditya Mahajan responsable
Shuang Gao responsable


Montréal Québec

Organisme associé

Centre for intelligent machines (CIM)

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