818 research outputs found
Security Games with Information Leakage: Modeling and Computation
Most models of Stackelberg security games assume that the attacker only knows
the defender's mixed strategy, but is not able to observe (even partially) the
instantiated pure strategy. Such partial observation of the deployed pure
strategy -- an issue we refer to as information leakage -- is a significant
concern in practical applications. While previous research on patrolling games
has considered the attacker's real-time surveillance, our settings, therefore
models and techniques, are fundamentally different. More specifically, after
describing the information leakage model, we start with an LP formulation to
compute the defender's optimal strategy in the presence of leakage. Perhaps
surprisingly, we show that a key subproblem to solve this LP (more precisely,
the defender oracle) is NP-hard even for the simplest of security game models.
We then approach the problem from three possible directions: efficient
algorithms for restricted cases, approximation algorithms, and heuristic
algorithms for sampling that improves upon the status quo. Our experiments
confirm the necessity of handling information leakage and the advantage of our
algorithms
An extended study on addressing defender teamwork while accounting for uncertainty in attacker defender games using iterative Dec-MDPs
Multi-agent teamwork and defender-attacker security games are two areas that are currently receiving significant attention within multi-agent systems research. Unfortunately, despite the need for effective teamwork among multiple defenders, little has been done to harness the teamwork 1 research in security games. The problem that this paper seeks to solve is the coordination of decentralized defender agents in the presence of uncer-tainty while securing targets against an observing adversary. To address this problem, we offer the following novel contributions in this paper: (i) New model of security games with defender teams that coordinate under uncertainty; (ii) New algorithm based on column generation that uti-lizes Decentralized Markov Decision Processes (Dec-MDPs) to generate defender strategies that incorporate uncertainty; (iii) New techniques to handle global events (when one or more agents may leave the system) during defender execution; (iv) Heuristics that help scale up in the num-ber of targets and agents to handle real-world scenarios; (v) Exploration of the robustness of randomized pure strategies. The paper opens the door to a potentially new area combining computational game theory and multi-agent teamwork.
INTEROPERABILITY FOR MODELING AND SIMULATION IN MARITIME EXTENDED FRAMEWORK
This thesis reports on the most relevant researches performed during the years of the Ph.D. at the Genova University and within the Simulation Team. The researches have been performed according to M&S well known recognized standards. The studies performed on interoperable simulation cover all the environments of the Extended Maritime Framework, namely Sea Surface, Underwater, Air, Coast & Land, Space and Cyber Space. The applications cover both the civil and defence domain. The aim is to demonstrate the potential of M&S applications for the Extended Maritime Framework, applied to innovative unmanned vehicles as well as to traditional assets, human personnel included. A variety of techniques and methodology have been fruitfully applied in the researches, ranging from interoperable simulation, discrete event simulation, stochastic simulation, artificial intelligence, decision support system and even human behaviour modelling
A Polynomial Time Algorithm for Spatio-Temporal Security Games
An ever-important issue is protecting infrastructure and other valuable
targets from a range of threats from vandalism to theft to piracy to terrorism.
The "defender" can rarely afford the needed resources for a 100% protection.
Thus, the key question is, how to provide the best protection using the limited
available resources. We study a practically important class of security games
that is played out in space and time, with targets and "patrols" moving on a
real line. A central open question here is whether the Nash equilibrium (i.e.,
the minimax strategy of the defender) can be computed in polynomial time. We
resolve this question in the affirmative. Our algorithm runs in time polynomial
in the input size, and only polylogarithmic in the number of possible patrol
locations (M). Further, we provide a continuous extension in which patrol
locations can take arbitrary real values. Prior work obtained polynomial-time
algorithms only under a substantial assumption, e.g., a constant number of
rounds. Further, all these algorithms have running times polynomial in M, which
can be very large
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