John P. Sullivan

TL;DR: This paper presents TRUSTS, an application for scheduling randomized patrols for fare inspection in transit systems, an efficient algorithm for computing such patrol strategies and presents experimental results using real-world ridership data from the Los Angeles Metro Rail system.

TL;DR: TRUSTS as discussed by the authors models the problem of computing patrol strategies as a leader-follower Stackelberg game, where the objective is to deter fare evasion and hence maximize revenue.

TL;DR: This paper presents a novel general Bayesian Stackelberg game model for security resource allocation in dynamic uncertain domains, and presents results from a real-world experiment on Metro trains in Los Angeles validating the MDP-based model, and most importantly, concretely measuring the benefits of SSGs forSecurity resource allocation.

TL;DR: In this article, the authors examine the dynamics of transnational organized crime in Mexico and examine the exploitation of weak governance and areas (known as "lawless zones," "ungoverned spaces," "other governed spaces," or "zones of impunity") where state challengers have created parallel or dual sovereignty, or 'criminal enclaves' in a neo-feudal political arrangement.

TL;DR: The nature of crime and conflict has changed and continues to evolve as discussed by the authors, and the now and future war is and will be influenced by irregular combatants that utilize technology and net-computing.