Asymmetric-Information Resource Allocation Games: An LP Approach to Purposeful Deception

2026-04-27

AI Summary

This study addresses the strategic use of deception to protect critical assets by deliberately influencing attacker behavior. The defender allocates resources between genuine assets and decoys to manipulate the attacker’s beliefs, deploying deception only when it enhances defensive utility. The work formally introduces the concept of “purposeful deception” within a Bayesian game-theoretic framework and analyzes equilibrium strategies using perfect Bayesian Nash equilibrium. A novel, non-iterative linear programming approach is proposed to jointly optimize defense strategies and belief manipulation efficiently. Numerical experiments demonstrate that the method naturally balances resource allocation efficiency with effective belief control, yielding rational and goal-directed deceptive behaviors that adaptively respond to adversarial incentives.

Abstract

In this work, we introduce the Deceptive Resource Allocation Game (DRAG), which studies purposeful deception within a Bayesian game framework. In DRAG, a Defender allocates resources across the true asset and several decoys to influence an Attacker's beliefs and actions, with the goal of diverting the Attacker away from the true asset. We seek to characterize purposeful deception, whereby the Defender deceives only when doing so improves its performance. To this end, we solve for the Perfect Bayesian Nash Equilibrium (PBNE) of the corresponding game. We show that, despite the coupled belief-policy interdependence, the problem admits an efficient, non-iterative linear programming formulation. Numerical results demonstrate that the resulting policies naturally balance effective allocation and belief manipulation, giving rise to purposeful and emergent deceptive behaviors.

Problem

• Deceptive Resource Allocation
• Asymmetric Information
• Purposeful Deception
• Bayesian Game
• Perfect Bayesian Nash Equilibrium

Innovation

• Deceptive Resource Allocation Game
• Perfect Bayesian Nash Equilibrium
• Linear Programming
• Purposeful Deception
• Asymmetric Information