In this work, we study the problem of detecting risk-averse low-diameter clusters, modeled as k-clubs, in graphs. It is assumed that the uncertainty of the information associated with vertices is shown by stochastic weights, whose joint distribution is known. The goal is to find a k-club of minimum risk contained in the graph. A stochastic programming framework that is based on the formalism of...

Risk-averse multistage stochastic programs appear in multiple areas and are challenging to solve. Stochastic Dual Dynamic Programming (SDDP) is a well-known tool address such problems under time-independence assumptions. We show how derive dual formulation for these apply an SDDP algorithm, leading converging deterministic upper bounds risk-averse problems.

Heterogeneously risk-averse individuals who lack access to formal insurance build and use relationships with each other to manage risk. I show that the composition of equilibrium relationships under pairwise matching and when group size is endogenous is determined by a mean-variance trade-o¤ across di¤erentially risky productive opportunities, though output distributions may have in…nitely-many...

We study the dynamic general equilibrium of an economy where risk averse shareholders delegate the management of the firm to risk averse managers. The optimal contract has two main components: an incentive component corresponding to a non-tradable equity position and a variable “salary” component indexed to the aggregate wage bill and to aggregate dividends. Tying a manager’s compensation to th...

In this paper we present and validate a novel attacker model based on the economic notion that the attacker has limited resources to forge a new attack. We focus on the vulnerability exploitation case, whereby the attacker has to choose whether to exploit a new vulnerability or keep an old one. We postulate that most vulnerabilities remain unattacked, and that the exploit development cycle rela...

Imitation learning algorithms learn viable policies by imitating an expert’s behavior when reward signals are not available. Generative Adversarial Imitation Learning (GAIL) is a state-of-the-art algorithm for learning policies when the expert’s behavior is available as a fixed set of trajectories. We evaluate in terms of the expert’s cost function and observe that the distribution of trajector...

We consider a slotted-ALOHA LAN with loss-averse, noncooperative greedy users. To avoid non-Pareto equilibria, particularly deadlock, we assume probabilistic loss-averse behavior. This behavior is modeled as a modulated white noise term, in addition to the greedy term, creating a diffusion process modeling the game. We observe that when player’s modulate with their throughput, a more efficient ...

This paper explores people’s behavior when they are facing financial risks. Through the setting of an economics experiment, people’s willingness to bear financial risks and their tendency to impose risks on others are investigated. The experiment result shows that most people are risk-neutral or risk-averse when making decision under financial environment, and their tendency to impose risks on ...

Drosophila melanogaster postfeeding larvae show food-averse migration toward food-free habitats before metamorphosis. This developmental switching from food attraction to aversion is regulated by a neuropeptide Y (NPY)-related brain signaling peptide. We used the fly larva model to delineate the neurobiological basis of age-restricted response to environmental stimuli. Here we provide evidence ...

Accident Risk, Gender, Family Status and Occupational Choice in the UK Many studies show that women are more risk averse than men. In this paper, following DeLeire and Levy (2004) for the US, we use family structure as a proxy for the degree of risk aversion to test the proposition that those with strong aversion to risk will make occupational choices biased towards safer jobs. In line with DeL...