@conference {18922,
	title = {The Life Game: Cognitive Strategies for Repeated Stochastic Games},
	year = {2011},
	month = {2011/10//},
	pages = {95 - 102},
	abstract = {Standard models in bio-evolutionary game theory involve repetitions of a single stage game (e.g., the Prisoner{\textquoteright}s Dilemma or the Stag Hunt); but it is clear that repeatedly playing the same stage game is not an accurate model of most individuals{\textquoteright} lives. Rather, individuals{\textquoteright} interactions with others correspond to many different kinds of stage games. In this work, we concentrate on discovering behavioral strategies that are successful for the life game, in which the stage game is chosen stochastically at each iteration. We present a cognitive agent model based on Social Value Orientation (SVO) theory. We provide extensive evaluations of our model{\textquoteright}s performance, both against standard agents from the game theory literature and against a large set of life-game agents written by students in two different countries. Our empirical results suggest that for life-game strategies to be successful in environments with such agents, it is important (i) to be unforgiving with respect to trust behavior and (ii) to use adaptive, fine-grained opponent models of the other agents.},
	keywords = {adaptive model, behavioral strategy, bioevolutionary game theory, cognitive agent model, fine-grained opponent model, game theory, iteration, iterative methods, life game, prisoner{\textquoteright}s dilemma, repeated stochastic games, social value orientation theory, stag hunt, stage game, Stochastic processes, trust behavior},
	doi = {10.1109/PASSAT/SocialCom.2011.62},
	author = {Cheng,Kan-Leung and Zuckerman,I. and Nau, Dana S. and Golbeck,J.}
}
@conference {17751,
	title = {A graph-theoretic approach to protect static and moving targets from adversaries},
	booktitle = {Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1},
	series = {AAMAS {\textquoteright}10},
	year = {2010},
	month = {2010///},
	pages = {299 - 306},
	publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
	organization = {International Foundation for Autonomous Agents and Multiagent Systems},
	address = {Richland, SC},
	abstract = {The static asset protection problem (SAP) in a road network is that of allocating resources to protect vertices, given any possible behavior by an adversary determined to attack those assets. The dynamic asset protection (DAP) problem is a version of SAP where the asset is following a fixed and widely known route (e.g., a parade route) and needs to be protected. We formalize what it means for a given allocation of resources to be "optimal" for protecting a desired set of assets, and show that randomly allocating resources to a single edge cut in the road network solves this problem. Unlike SAP, we show that DAP is not only an NP-complete problem, but that approximating DAP is also NP-hard. We provide the GreedyDAP heuristic algorithm to solve DAP and show experimentally that it works well in practice, using road network data for real cities.},
	keywords = {adversarial reasoning, agent systems, game theory},
	isbn = {978-0-9826571-1-9},
	url = {http://dl.acm.org/citation.cfm?id=1838206.1838248},
	author = {Dickerson,J. P. and Simari,G. I and V.S. Subrahmanian and Kraus,Sarit}
}
@article {16404,
	title = {The emergence of zoning policy games in exurban jurisdictions: Informing collective action theory},
	journal = {Land Use Policy},
	volume = {26},
	year = {2009},
	month = {2009/04//},
	pages = {356 - 367},
	abstract = {Theoretical urban policy literature predicts the likelihood of free riding in the management of common goods such as forested open space; such outcome is often characterized as a Prisoner{\textquoteright}s Dilemma game. Numerous cases exist in which neighboring jurisdictions cooperate to maintain public goods, challenging the expected results, yet theoretical explanations of these cases have not been fully developed. In this paper, we use an agent-based model to explore how underlying micro-behaviors affect the payoffs obtained by two neighboring municipalities in a hypothetical exurban area. Payoffs are measured in terms of regional forested space and of local tax revenue at the end of the agent-based simulations; the municipalities affect these payoffs through their choice of residential zoning policies and the spillover effect between the neighboring jurisdictions. Zoning restrictions influence the conversion of farmland into residential subdivisions of different types, and consequently the location of heterogeneous residential households in the region. Developers and residents respond to the changing landscape characteristics, thus establishing a feedback between early and future land-use patterns. The structure of the simulated payoffs is analyzed using standard game theory. Our analysis shows that a variety of games, in addition to Prisoner{\textquoteright}s Dilemma, can emerge between the neighboring jurisdictions. Other games encourage coordination or subsidization, offering some explanations for the unexpected observations. The game realized in any given context depends on the initial characteristics of the landscape, the value given to the objectives each township seeks to maximize, and the income distribution of the population.},
	keywords = {Agent-based modeling, game theory, Land-use policy, Local government cooperation, Scale interaction},
	isbn = {0264-8377},
	doi = {10.1016/j.landusepol.2008.04.004},
	url = {http://www.sciencedirect.com/science/article/pii/S0264837708000604},
	author = {Zellner,Moira L. and Page,Scott E. and Rand, William and Brown,Daniel G. and Robinson,Derek T. and Nassauer,Joan and Low,Bobbi}
}
@article {18899,
	title = {Computational Cultural Dynamics},
	journal = {Intelligent Systems, IEEE},
	volume = {23},
	year = {2008},
	month = {2008/08//july},
	pages = {18 - 19},
	abstract = {Computational cultural dynamics blends the behavioral and social sciences - fields such as political science, psychology, journalism, anthropology, and sociology - with technological fields such as computer science, computational linguistics, game theory, statistical modeling, and operations research.},
	keywords = {anthropology, behavioral science, behavioural sciences computing, computational cultural dynamics, computational linguistics, Computer science, game theory, journalism, operations research, political science, Psychology, social sciences, social sciences computing, sociology, statistical modeling},
	isbn = {1541-1672},
	doi = {10.1109/MIS.2008.61},
	author = {Nau, Dana S. and Wilkenfeld,J.}
}
@conference {19032,
	title = {Detection of denial-of-message attacks on sensor network broadcasts},
	year = {2005},
	month = {2005},
	pages = {64 - 78},
	abstract = {So far sensor network broadcast protocols assume a trustworthy environment. However in safety and mission-critical sensor networks this assumption may not be valid and some sensor nodes might be adversarial. In these environments, malicious sensor nodes can deprive other nodes from receiving a broadcast message. We call this attack a denial-of-message attack (DoM). In this paper we model and analyze this attack, and present countermeasures. We present SIS, a secure implicit sampling scheme that permits a broadcasting base station to probabilistically detect the failure of nodes to receive its broadcast, even if these failures result from an attacker motivated to induce these failures undetectably. SIS works by eliciting authenticated acknowledgments from a subset of nodes per broadcast, where the subset is unpredictable to the attacker and tunable so as to mitigate acknowledgment implosion on the base station. We use a game-theoretic approach to evaluate this scheme in the face of an optimal attacker that attempts to maximize the number of nodes it denies the broadcast while remaining undetected by the base station, and show that SIS significantly constrains such an attacker even in sensor networks exhibiting high intrinsic loss rates. We also discuss extensions that permit more targeted detection capabilities.},
	keywords = {authenticated acknowledgments, broadcast channels, broadcast protocols, broadcasting base station, countermeasures, denial-of-message attacks, DoM, game theory, game-theoretic approach, malicious sensor nodes, Mobile computing, optimal attacker, probabilistic detection, probability, Protocols, Sampling methods, secure implicit sampling, sensor network broadcasts, SIS, telecommunication security, Wireless sensor networks},
	author = {McCune, J.M. and Elaine Shi and Perrig, A. and Reiter, M.K.}
}
