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.

翻译：本文提出“欺骗性资源配置博弈”（Deceptive Resource Allocation Game, DRAG），在贝叶斯博弈框架下系统研究有目的欺骗行为。博弈中，防御方将资源分配至真实资产与若干诱饵之间，旨在影响攻击方的信念与行动，从而将其引离真实资产。我们试图刻画有目的欺骗的特征——即防御方仅在能够改善自身表现时实施欺骗。为此，我们求解了该博弈的完美贝叶斯纳什均衡（Perfect Bayesian Nash Equilibrium, PBNE）。研究表明，尽管信念与策略存在耦合关联，该问题仍可转化为高效的非迭代线性规划形式。数值结果验证了所得策略能自然平衡有效资源配置与信念操纵，从而涌现出兼具目的性与自发性的欺骗行为。