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Found 7 papers, 0 papers with code
Computing the Strategy to Commit to in Polymatrix Games (Extended Version)
We study the computational complexity of finding or approximating an optimistic or pessimistic leader-follower equilibrium in specific classes of succinct games---polymatrix like---which are equivalent to 2-player Bayesian games with uncertainty over the follower, with interdependent or independent types.
How to Maximize the Spread of Social Influence: A Survey
This survey presents the main results achieved for the influence maximization problem in social networks.
Facing Multiple Attacks in Adversarial Patrolling Games with Alarmed Targets
We show that even the error of just a single resource can lead to an arbitrary inefficiency, when the inefficiency is defined as the ratio of the Defender's utilities obtained with a wrong guess and a correct guess.
Team-maxmin equilibrium: efficiency bounds and algorithms
The Team-maxmin equilibrium prescribes the optimal strategies for a team of rational players sharing the same goal and without the capability of correlating their strategies in strategic games against an adversary.
Machine Learning Techniques for Stackelberg Security Games: a Survey
The present survey aims at presenting the current machine learning techniques employed in security games domains.
Multi-resource defensive strategies for patrolling games with alarm systems
The central problem with an alarm system, unexplored in other Security Games, is finding the best strategy to respond to alarm signals for each mobile defensive resource.
Adversarial patrolling with spatially uncertain alarm signals
That is, the alarm system is able to detect an attack but it is uncertain on the exact position where the attack is taking place.
