@conference {1502505,
	title = {Conducting Longitudinal Experiments with Behavioral Models in Repeated Stackelberg Security Games on Amazon Mechanical Turk },
	booktitle = {Human-Agent Interaction Design and Models (HAIDM) Workshop at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2015)},
	year = {2015},
	abstract = {Recently, there has been an increase of interest in domains involving
repeated interactions between defenders and adversaries. This has been modeled
as a repeated Stackelberg Security Game (repeated SSG). Although different behavioral models have been proposed for the attackers in these games, human subjects experiments for testing these behavioral models in repeated SSGs have not
been conducted previously. This paper presents the first {\textquotedblleft}longitudinal study{\textquotedblright} {\textendash} at
least in the context of SSGs {\textendash} of testing human behavior models in repeated SSG
settings. We provide the following contributions in this paper. First, in order to
test the behavioral models, we design a game that simulates the repeated interactions between the defender and the adversary and deploy it on Amazon Mechanical Turk (AMT). Human subjects are asked to participate in this repeated
task in rounds of the game, with a break between consecutive rounds. Second,
we develop several approaches to keep the human subjects motivated throughout
the course of this longitudinal study so that they participate in all measurement
occasions, thereby minimizing attrition. We provide results showing improvements of retention rate due to implementation of these approaches. Third, we
propose a way of choosing representative payoffs that fit the real-world scenarios
as conducting these experiments are extremely time-consuming and we can only
conduct a limited number of such experiments.},
	author = {Kar, Debarun and Fang, Fei and Delle Fave, Francesco and Sintov, Nicole and Tambe, Milind}
}
