@conference {1501442,
	title = {SPECTRE: A Game Theoretic Framework for Preventing Collusion in Security Games (Demonstration) },
	booktitle = {International conference on Autonomous Agents and Multiagent Systems (AAMAS)},
	year = {2016},
	abstract = {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 destructive cooperation mechanism between adversaries. SPECTRE (Strategic Patrol
planner to Extinguish Collusive ThREats) takes into account the synergistic destructive collusion among two groups
of adversaries in security games. This framework is designed for the purpose of efficient patrol scheduling for security agents in security games in presence of collusion and
is mainly build up on game theoretic approaches, optimization techniques, machine learning methods and theories for
human decision making under risk. The major advantage of
SPECTRE is involving real world data from human subject
experiments with participants on Amazon Mechanical Turk
(AMT).},
	author = {Gholami, Shahrzad and Bryan Wilder and Brown, Matthew and Sinha, Arunesh and Sintov, Nicole and Tambe, Milind}
}
