A Game Theoretic Approach on Addressing Collusion among Human Adversaries


Shahrzad Gholami, Bryan Wilder, Matthew Brown, Arunesh Sinha, Nicole Sintov, and Milind Tambe. 2016. “A Game Theoretic Approach on Addressing Collusion among Human Adversaries .” In Workshop on security and multiagent systems, International conference on Autonomous Agents and Multiagent Systems (AAMAS).


Several models have been proposed for Stackelberg security games (SSGs) and protection against perfectly rational and bounded rational adversaries; however, none of these existing models addressed the collusion mechanism between adversaries. In a large number of studies related to SSGs, there is one leader and one follower in the game such that the leader takes action and the follower responds accordingly. These studies fail to take into account the possibility of existence of group of adversaries who can collude and cause synergistic loss to the security agents (defenders). The first contribution of this paper is formulating a new type of Stackleberg security game involving a beneficial collusion mechanism among adversaries. The second contribution of this paper is to develop a parametric human behavior model which is able to capture the bounded rationality of adversaries in this type of collusive games. This model is proposed based on human subject experiments with participants on Amazon Mechanical Turk (AMT).
See also: 2016