@conference {1499317,
	title = {When Players Affect Target Values: Modeling and Solving Dynamic Partially Observable Security Games},
	year = {2019},
	address = {Conference on Decision and Game Theory for Security, 2019},
	abstract = {Most of the current security models assume that the values of targets/areas are static or the changes (if any) are scheduled andknown to the defender. Unfortunately, such models are not sufficientfor many domains, where actions of the players modify the values ofthe targets. Examples include wildlife scenarios, where the attacker canincrease value of targets by secretly building supporting facilities. To address such security game domains with player-affected values, we firstpropose DPOS3G, a novel partially observable stochastic Stackelberggame where target values are determined by the players{\textquoteright} actions; the defender can only partially observe these targets{\textquoteright} values, while the attackercan fully observe the targets{\textquoteright} values and the defender{\textquoteright}s strategy. Second,we propose RITA (Reduced game Iterative Transfer Algorithm), whichis based on the heuristic search value iteration algorithm for partially observable stochastic game (PG-HSVI) and introduces three key novelties:(a) building a reduced game with only key states (derived from partitioning the state space) to reduce the numbers of states and transitionsconsidered when solving the game; (b) incrementally adding defender{\textquoteright}sactions to further reduce the number of transitions of the game; (c) providing novel heuristics for lower bound initialization of the algorithm.Third, we conduct extensive experimental evaluations of the algorithmsand the results show that RITA significantly outperforms the baselinePG-HSVI algorithm on scalability while allowing for trade off in scalability and solution quality.},
	author = {Xinrun Wang and Tambe, Milind and Branislav Boˇsansky ́ and An, Bo}
}
