Geodesic
Guaranteed solution for risk-neutral decision maker: an analog of maximin in single-criterion choice problem
Taurida Journal of Computer Science Theory and Mathematics, no. 2 (2023), pp. 7-29

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In this article single-criterion choice problems under uncertainty (SCPUs) are considered. The principle of minimax regret and the Savage-Niehans risk function are introduced. A possible approach to solving an SCPU for a decision-maker who simultaneously seeks to increase his outcome and reduce his risk (“to kill two birds with one stone”) is proposed. The explicit form of such a solution for the linear-quadratic setup of the SCPU is obtained.
Keywords: guaranteed solution, single-criterion choice, Savage-Niehans risk, minimax regret, uncertainties. 
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     author = {V. I. Zhukovskii and L. V. Zhukovskaya and Yu. S. Mukhina and S. P. Samsonov},
     title = {Guaranteed solution for risk-neutral decision maker: an analog of maximin in single-criterion choice problem},
     journal = {Taurida Journal of Computer Science Theory and Mathematics},
     pages = {7--29},
     publisher = {mathdoc},
     number = {2},
     year = {2023},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/TVIM_2023_2_a0/}
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V. I. Zhukovskii; L. V. Zhukovskaya; Yu. S. Mukhina; S. P. Samsonov. Guaranteed solution for risk-neutral decision maker: an analog of maximin in single-criterion choice problem. Taurida Journal of Computer Science Theory and Mathematics, no. 2 (2023), pp. 7-29. http://geodesic.mathdoc.fr/item/TVIM_2023_2_a0/