@article {1503281,
	title = {Improving Resource Allocation Strategies Against Human Adversaries in Security Games: An Extended Study },
	journal = {Artificial Intelligence Journal (AIJ)},
	number = {195},
	year = {2013},
	pages = {440-469},
	abstract = {Stackelberg games have garnered significant attention in recent years given
their deployment for real world security. Most of these systems, such as
ARMOR, IRIS and GUARDS have adopted the standard game-theoretical
assumption that adversaries are perfectly rational, which is standard in the
game theory literature. This assumption may not hold in real-world security
problems due to the bounded rationality of human adversaries, which could
potentially reduce the effectiveness of these systems.
In this paper, we focus on relaxing the unrealistic assumption of perfectly
rational adversary in Stackelberg security games. In particular, we present
new mathematical models of human adversaries{\textquoteright} behavior, based on using two
fundamental theory/method in human decision making: Prospect Theory
(PT) and stochastic discrete choice model. We also provide methods for
tuning the parameters of these new models. Additionally, we propose a
modification of the standard quantal response based model inspired by rankdependent expected utility theory. We then develop efficient algorithms to
compute the best response of the security forces when playing against the
different models of adversaries. In order to evaluate the effectiveness of the
new models, we conduct comprehensive experiments with human subjects
using a web-based game, comparing them with models previously proposed
in the literature to address the perfect rationality assumption on part of the
adversary.
Our experimental results show that the subjects{\textquoteright} responses follow the assumptions of our new models more closely than the previous perfect rationality assumption. We also show that the defender strategy produced by our
new stochastic discrete choice model outperform the previous leading contender for relaxing the assumption of perfect rationality.Furthermore, in a
separate set of experiments, we show the benefits of our modified stochastic
model (QRRU) over the standard model (QR).},
	author = {R. Yang and C. Kiekintvled and F. Ordonez and M. Tambe and R. John}
}
