Distributionally Robust Games with Risk-averse Players

Nicolas Loizou


We present a new model of incomplete information games without private information in which the players use a distributionally robust optimization approach to cope with the payoff uncertainty. With some specific restrictions, we show that our “Distributionally Robust Game” constitutes a true generalization of three popular finite games. These are the Complete Information Games, Bayesian Games and Robust Games. Subsequently, we prove that the set of equilibria of an arbitrary distributionally robust game with specified ambiguity set can be computed as the component-wise projection of the solution set of a multi-linear system of equations and inequalities. For special cases of such games we show equivalence to complete information finite games (Nash Games) with the same number of players and same action spaces. Thus, when our game falls within these special cases one can simply solve the corresponding Nash Game. Finally, we demonstrate the applicability of our new model of games and highlight its importance.


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Paper Citation

in Harvard Style

Loizou N. (2016). Distributionally Robust Games with Risk-averse Players . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 186-196. DOI: 10.5220/0005753301860196

in Bibtex Style

author={Nicolas Loizou},
title={Distributionally Robust Games with Risk-averse Players},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},

in EndNote Style

JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Distributionally Robust Games with Risk-averse Players
SN - 978-989-758-171-7
AU - Loizou N.
PY - 2016
SP - 186
EP - 196
DO - 10.5220/0005753301860196