Citation: Raicevich S, Battaglia P, Fortibuoni T, Romeo T, Giovanardi O and Andaloro F (2017) Critical Inconsistencies in Early Implementations of the Marine Strategy Framework Directive and Common Fisheries Policy Objectives Hamper Policy Synergies in Fostering the Sustainable Exploitation of Mediterranean Fisheries Resources. Front. Mar. Sci. 4:316. doi: 10.3389/fmars.2017.00316 Critical Inco...

Objective: To increase the positive and mitigate the negative health impacts of the mayor’s draft transport strategy for London. Design: A rapid prospective health impact assessment (HIA) of the penultimate draft of the strategy, using a review commissioned by the regional director of public health; an appraisal of congestion charging; and a participatory workshop. Two audits of changes were pe...

OBJECTIVE To increase the positive and mitigate the negative health impacts of the mayor's draft transport strategy for London. DESIGN A rapid prospective health impact assessment (HIA) of the penultimate draft of the strategy, using a review commissioned by the regional director of public health; an appraisal of congestion charging; and a participatory workshop. Two audits of changes were pe...

Speed limit policy, a monetary policy strategy that focuses on stabilizing inflation and the change in the output gap, consistently delivers better welfare outcomes than flexible inflation targeting or flexible price level targeting in empirical New Keynesian models when policymakers lack the ability to commit to future policies. Even if the policymaker can commit under an inflation targeting s...

The AARP Public Policy Institute, formed in 1985, is part of the Policy and Strategy group at AARP. One of the missions of the Institute is to foster research and strategy on public policy issues of importance to mid-life and older Americans. This publication represents part of that effort. The views expressed herein are for information, debate, and discussion and do not necessarily represent o...

Policy search is a subfield in reinforcement learning which focuses on finding good parameters for a given policy parametrization. It is well suited for robotics as it can cope with high-dimensional state and action spaces, one of the main challenges in robot learning. We review recent successes of both model-free and model-based policy search in robot learning. Model-free policy search is a ge...