SAFE Newsletter : 2013, Q3

Research: Joachim Weber, Benjamin Loos, Steffen Meyer, Andreas Hackethal "Individual Investors' Trading Motives and Security Selling Behavior" Ignazio Angeloni, Ester Faia "Monetary Policy and Prudential Regulations with Bank Runs" Helmut Siekmann "Legal Limits to Quantitative Easing" Policy Margit Vanberg "SAFE Summer Academy 2013 on 'International Financial Stability'" Guest Commentary Peter Praet "Cooperation between the ECB and Academia

The Safe-Port project: an approach to port surveillance and protection

SAFE-PORT is a recently started project addressing the complex issue of determining the best configurations of resources for harbour and port surveillance and protection. More specifically, the main goal is to find, for any given scenario, an adequate set of configuration solutions — i.e., number and type of sensors and equipments, their locations and operating modes, the corresponding personnel and other support resources — that maximize protection over a specific area. The project includes research and development of sensors models, novel algorithms for optimization and decision support, and a computer-based decision support system (DSS) to assist decision makers in that task. It includes also the development of a simulation environment for modelling relevant aspects of the scenario (including sensors used for surveillance, platforms, threats and the environment), capable to incorporate data from field-trials, used to test and validate solutions proposed by the DSS. Test cases will consider the use of intelligent agents to model the behaviour of threats and of NATO forces in a realistic way, following experts’ definitions and parameters

Building safe software

Murphy is a set of techniques and tools under investigation for their potential in enhancing the safety of software. This paper describes some of the work which has been done and some which is planned

Better safe than sorry: Risky function exploitation through safe optimization

Exploration-exploitation of functions, that is learning and optimizing a mapping between inputs and expected outputs, is ubiquitous to many real world situations. These situations sometimes require us to avoid certain outcomes at all cost, for example because they are poisonous, harmful, or otherwise dangerous. We test participants' behavior in scenarios in which they have to find the optimum of a function while at the same time avoid outputs below a certain threshold. In two experiments, we find that Safe-Optimization, a Gaussian Process-based exploration-exploitation algorithm, describes participants' behavior well and that participants seem to care firstly whether a point is safe and then try to pick the optimal point from all such safe points. This means that their trade-off between exploration and exploitation can be seen as an intelligent, approximate, and homeostasis-driven strategy.Comment: 6 pages, submitted to Cognitive Science Conferenc

Safe Passage

Most young people make the transition from adolescence to adulthood with the support of their families, communities, and schools. However, 5.4 million of our nation's most vulnerable youth -- youth aging out of foster care, teenage parents, out-of-school students and those in danger of dropping out, and youth involved in the juvenile justice system -- lack the services and social supports they need to succeed as productive workers, responsible parents, and engaged citizens. Fortunately, a host of social ills -- from violence and urban decay to persistent poverty and homelessness to lost wages and the high costs of incarceration -- can be prevented by investing in cost-effective community supports that help young people who are, or who are in danger of becoming, disconnected. The strategies outlined in the YTFG publication Safe Passage highlight some of the ways we can make more prudent and effective investments in our young people