A Zero-Sum Game with Two Players

Alexander Zaslavski
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Alexander Zaslavski: Israel Institute of Technology

Chapter Chapter 8 in Convex Optimization with Computational Errors, 2020, pp 259-275 from Springer

Abstract: Abstract In this chapter we study an algorithm for finding a saddle point of a zero-sum game with two players. For this algorithm each iteration consists of two steps. The first step is a calculation of a subgradient while the second one is a proximal gradient step. In each of these two steps there is a computational error. In general, these two computational errors are different. We show that our algorithm generates a good approximate solution, if all the computational errors are bounded from above by a small positive constant. Moreover, if we know the computational errors for the two steps of our algorithm, we find out what approximate solution can be obtained and how many iterates one needs for this.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-37822-6_8

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DOI: 10.1007/978-3-030-37822-6_8

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