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Séminaire informel de théorie des systèmes (ISS)

Discrete-time zero-sum games for Markov chains with risk-sensitive average cost criterion


10 mai 2024   10h30 — 11h30

Subrata Golui Indian Institute of Technology Bombay, Inde

Subrata Golui

Séminaire hybride à l'Université McGill ou Zoom.

We study zero-sum stochastic games for controlled discrete time Markov chains with risk-sensitive average cost criterion with countable/compact state space and Borel action spaces. The payoff function is nonnegative and possibly unbounded for a countable state space case and for a compact state space case, it is a real-valued and bounded function. For the countable state space case, under a certain Lyapunov-type stability assumption on the dynamics we establish the existence of the value and a saddle point equilibrium. For the compact state space case, we establish these results without any Lyapunov-type stability assumptions. Using the stochastic representation of the principal eigenfunction of the associated optimality equation, we completely characterize all possible saddle point strategies in the class of stationary Markov strategies.

Bio: My name is Subrata Golui and I am a postdoctoral fellow in the Department of Mathematics, Indian Institute of Technology, Bombay. I obtained PhD degree at Indian Institute of Technology Guwahati under the supervision of Dr. Chandan Pal on 5th July 2023. My thesis title is Risk-sensitive stochastic control and games. My research interests can be broadly classified into three areas: stochastic control theory, stochastic game theory, and queueing theory. Currently, I am working on the stochastic control theory. More specifically, I am studying the metastable behaviour exhibited by the Markov processes. I have 8 published articles and one more self-authored research work has been submitted for publication.

Peter E. Caines responsable
Aditya Mahajan responsable
Shuang Gao responsable
Borna Sayedana responsable
Alex Dunyak responsable


Salle MC 437
Pavillon McConnell
Université McGill
3480, rue University
Montréal QC H3A 0E9

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Centre for intelligent machines (CIM)

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