Zero-sum Risk-sensitive Stochastic Games for Continuous Time Markov Chains
Optimization and Control
2016-03-09 v1
Abstract
We study infinite horizon discounted-cost and ergodic-cost risk-sensitive zero-sum stochastic games for controlled continuous time Markov chains on a countable state space. For the discounted-cost game we prove the existence of value and saddle-point equilibrium in the class of Markov strategies under nominal conditions. For the ergodic-cost game we prove the existence of values and saddle point equilibrium by studying the corresponding Hamilton-Jacobi-Isaacs equation under a certain Lyapunov condition.
Keywords
Cite
@article{arxiv.1603.02400,
title = {Zero-sum Risk-sensitive Stochastic Games for Continuous Time Markov Chains},
author = {Mrinal K. Ghosh and K. Suresh Kumar and Chandan Pal},
journal= {arXiv preprint arXiv:1603.02400},
year = {2016}
}