Bilevel optimization is a very active field of applied mathematics. The main reason is that
bilevel optimization problems can serve as a powerful tool for modeling hierarchical …

Bilevel optimization is a field of mathematical programming in which some variables are
constrained to be the solution of another optimization problem. As a consequence, bilevel …

The failure of a power system as a critical infrastructure causes considerable damage to
society. Hence, the vulnerabilities of such facilities should be minimized to cope with several …

Generative Adversarial Networks (GANs) are a type of generative model which have
received much attention due to their ability to model complex real-world data. Despite their …

The sports domain presents a number of significant computational challenges for artificial
intelligence (AI) and machine learning (ML). In this paper, we explore the techniques that …

Artificial intelligence for social good (AI4SG) is a research theme that aims to use and
advance artificial intelligence to address societal issues and improve the well-being of the …

Abstract Purpose of Review Robotic patrolling aims at protecting a physical environment by
deploying a team of one or more autonomous mobile robots in it. A key problem in this …

Stackelberg equilibria arise naturally in a range of popular learning problems, such as in
security games or indirect mechanism design, and have received increasing attention in the …

A decision support system for cyber-security is here presented. The system aims to select an
optimal portfolio of security controls to counteract multi-stage attacks. The system has …

In the last fifty years, researchers have developed statistical, data-driven, analytical, and
algorithmic approaches for designing and improving emergency response management …