2020/02/01 by Giovanni P. Crespi, Crespi, Giovanni Paolo, Davide Radi +3 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · #91A10 #Climate Change Policy and Economics #Computer Science and Game Theory (cs.GT) #Decision-Making and Behavioral Economics #Economic and Environmental Valuation #FOS: Computer and information sciences #FOS: Economics and business #J.4 #Theoretical Economics (econ.TH)
paper · doi:10.48550/arxiv.2002.00225
openalex publication_date 2020/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
A robust game is a distribution-free model to handle ambiguity generated by a bounded set of possible realizations of the values of players' payoff functions. The players are worst-case optimizers and a solution, called robust-optimization equilibrium, is guaranteed by standard regularity conditions. The paper investigates the sensitivity to the level of uncertainty of this equilibrium. Specifically, we prove that it is an epsilon-Nash equilibrium of the nominal counterpart game, where the epsilon-approximation measures the extra profit that a player would obtain by reducing his level of uncertainty. Moreover, given an epsilon-Nash equilibrium of a nominal game, we prove that it is always possible to introduce uncertainty such that the epsilon-Nash equilibrium is a robust-optimization equilibrium. An example shows that a robust Cournot duopoly model can admit multiple and asymmetric robust-optimization equilibria despite only a symmetric Nash equilibrium exists for the nominal counterpart game.