Pedestrian movements in crowd motion can be perceived in terms of agents who basically exhibit patient or impatient behavior. We model crowd motion subject to exit congestion under uncertainty conditions in a continuous space and compare the proposed model via simulations with the classical social force model. During a typical emergency evacuation scenario, agents might not be able to perceive ...

BACKGROUND Research on the neural correlates of risk-related behaviors and personality traits has provided insight into mechanisms underlying both normal and pathological decision-making. Task-based neuroimaging studies implicate a distributed network of brain regions in risky decision-making. What remains to be understood are the interactions between these regions and their relation to individ...

Governments and their regulatory agencies normally exhibit risk-neutral attitudes in their decision-making. However, for low probability-high consequence events many decision-makers tend to be risk-averse because of the catastrophic or dire nature of the hazard or event. The degree of risk averseness can be described by utility theory. This paper will infer utility functions that reflect the le...

A nonstandard probabilistic setting for modeling of the risk of catastrophic events is presented. It allows random variables to take on infinitely large negative values with non-zero probability, which corresponds to catastrophic consequences unmeasurable in monetary terms, e.g. loss of human lives. Thanks to this extension, the safety-first principle is proved to be consistent with traditional...

Risk averse stochastic optimization is investigated in the context of elastic shape optimization, allowing for microstructures in the admissible shapes. In particular, a two-stage model for shape optimization under stochastic loading with risk averse cost functionals is combined with a two-scale approach for the simulation of microstructured materials. The microstructure is composed of an elast...

We introduce the concept of a Markov risk measure and we use it to formulate risk-averse control problems for two Markov decision models: a finite horizon model and a discounted infinite horizon model. For both models we derive risk-averse dynamic programming equations and a value iteration method. For the infinite horizon problem we also develop a risk-averse policy iteration method and we pro...

Economic forces shape the behavior of individuals and institutions. Forces affecting individual behavior are attitudes about payoffs (gains and losses) and beliefs about outcomes (risk and ambiguity). Under risk, the likelihoods of alternative outcomes are fully known. Under ambiguity, these likelihoods are unknown. In our experiment, payoffs and outcomes were manipulated independently during a...

We use Markov risk measures to formulate a risk-averse version of the undiscounted total cost problem for a transient controlled Markov process. We derive risk-averse dynamic programming equations and we show that a randomized policy may be strictly better than deterministic policies, when risk measures are employed. We illustrate the results on an optimal stopping problem and an organ transpla...