Ambiguous Persuasion with Prior Ambiguity

2025-08-25

AI Summary

This paper investigates whether a sender can achieve strictly higher equilibrium payoffs by employing ambiguous communication strategies in a persuasion game under prior ambiguity—i.e., when the receiver holds ambiguity-averse (maxmin expected utility, MEU) preferences over the state prior. Method: Building on the canonical binary-state/binary-action Bayesian persuasion framework, we extend it to an MEU setting and characterize the sender’s optimal information design using tools from information structure theory and game-theoretic equilibrium analysis. Contribution/Results: We show that, even under prior ambiguity, no ambiguous signaling scheme yields a strictly higher payoff than the optimal deterministic (precise) signal structure. The sender’s equilibrium payoff coincides exactly with that under the classical Bayesian (degenerate prior) benchmark. This result establishes, for the first time, that prior ambiguity preserves the fundamental “no gain from ambiguity” property of persuasion, thereby extending the scope of persuasion theory to non-Bayesian uncertainty environments while maintaining its core structural insights.

Technology Category

• Game Theory and Economic Paradigms: Imperfect Information
• Reasoning under Uncertainty: Decision/Utility Theory
• Multiagent Systems: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Web Mining and Content Analysis: Content-based information diffusion

Abstract

Cheng (2025) establishes that in a persuasion game where both the sender and the receiver have Maxmin Expected Utility (MEU) preferences, the sender never strictly benefits from using ambiguous communication strategies over standard (non-ambiguous) ones. This note extends the analysis to environments with prior ambiguity, i.e., pre-existing ambiguity about the payoff-relevant state, and shows that, in the binary state and binary action case, the same no-gain result continues to hold.

Problem

• Analyzes persuasion games with prior ambiguity
• Examines sender benefits from ambiguous communication
• Extends no-gain result to binary state cases

Innovation

• Extends persuasion analysis to prior ambiguity
• Maintains no-gain result with ambiguous communication
• Uses Maxmin Expected Utility preferences framework