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Author: Nicolas Loizou

Affiliation: University of Edinburgh, United Kingdom

ISBN: 978-989-758-171-7

Keyword(s): Game Theory, Equilibrium, Distributionally Robust Optimization, Conditional Value at Risk.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Game Theory ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Methodologies and Technologies ; Operational Research ; Optimization ; Symbolic Systems

Abstract: 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 hig hlight its importance. (More)

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Paper citation in several formats:
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

@conference{icores16,
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,},
year={2016},
pages={186-196},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005753301860196},
isbn={978-989-758-171-7},
}

TY - CONF

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

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