GTMAJun 27

Pure Nash Equilibria under the Affine Mechanism: A Potential Game of Exaggeration

arXiv:2606.290104.4
Predicted impact top 64% in GT · last 90 daysOriginality Incremental advance
AI Analysis

Provides theoretical understanding of strategic misreporting in widely used non-incentive-compatible mechanisms, relevant to mechanism design and game theory.

The paper characterizes pure Nash equilibria for the affine mechanism (including the mean mechanism) in both complete-information and Bayesian games, showing that extreme exaggeration is inevitable.

The mean mechanism is known to be non-incentive-compatible, namely, rational players are incentivized to misreport their values. Despite this game-theoretic issue, the mean mechanism is prevalent in practice due to its other desirable properties. We give a full characterization of pure Nash equilibria--how the players will misreport--for the affine mechanism, of which the mean is a special case. Furthermore, we characterize both complete-information and Bayesian games under the affine mechanism. Our results highlight the inevitability of extreme exaggeration in such games.

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