@conference {1504452,
	title = {Designing Better Strategies against Human Adversaries in Network Security Games: Extended Abstract },
	booktitle = {International Conference on Autonomous Agents and Multiagent Systems (AAMAS)(Short paper)	},
	year = {2012},
	abstract = {In a Network Security Game (NSG), security agencies must allocate limited resources to protect targets embedded in a network,
such as important buildings in a city road network. A recent line
of work relaxed the perfect-rationality assumption of human adversary and showed significant advantages of incorporating the bounded rationality adversary models in non-networked security domains. Given that real-world NSG are often extremely complex and
hence very difficult for humans to solve, it is critical that we address
human bounded rationality when designing defender strategies. To
that end, the key contributions of this paper include: (i) comprehensive experiments with human subjects using a web-based game
that we designed to simulate NSGs; (ii) new behavioral models of
human adversary in NSGs, which we train with the data collected
from human experiments; (iii) new algorithms for computing the
defender optimal strategy against the new models.},
	author = {Yang, Rong and Fang, Fei and Xin Jiang, Albert and Karthik Rajagopal and Tambe, Milind and Maheswaran, Rajiv}
}
