Year: 2025
Type: preprint
Abstract: This paper is an attempt to compute the value and saddle points of zero-sum risk-sensitive average stochastic games. For the average games with finite states and actions, we first introduce the so-called irreducibility coefficient and then establish its equivalence to the irreducibility condition. Using this equivalence,we develop an iteration algorithm to compute $\varepsilon$-approximations of the value (for any given $\varepsilon>0$) and show its convergence. Based on $\varepsilon$-approximations of the value and the irreducibility coefficient, we further propose another iteration algorithm, which is proved to obtain $\varepsilon$-saddle points in finite steps. Finally, a numerical example of energy management in smart grids is provided to illustrate our results.
Source: arXiv (Cornell University)
Authors: Chen, Fang, Guo, Xianping, Guo, Xin, Zhang, Junyu
Institutions: Peking University, Sun Yat-sen University
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
Award: G2671578558
OpenAlex ID: W4416014071
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