... a compiler framework designed to support transparent, lifelong program analysis and transformation for arbitrary programs, by providing high-level information to compiler transformations at compile-time, link-time, run-time, and in idle time between runs. LLVM defines a common, low-level code

needs basically financial operativeness, while on the contrary analysis in progress detach for economy the crucial contributions of training. This last, in fact, is the most able to generate relevant changes concerning production and transfer of knowledge and innovation. The present essay investigates

to collaboration. In this paper we provide an analysis of lifelong learning with respect to collaborative learning. In order to support the variety of collaboration modes and learning methods in lifelong learning scenarios, existing approaches to learning infrastructures must be extended in a number of directions

This paper is intended to provide a background analysis of research into adult learning and well-being, in advance of the NIACE seminar. Well-being and happiness have attracted increasing scholarly attention in recent years. There also seems to be a wider

discursive analysis of the skills and knowledge requirements of an emerging green knowledge based economy using a range of policy focussed and academic research literature Findings: The business opportunities that are emerging as a more sustainable world is developed requires the knowledge and skills

Policy makers place increasing emphasis on the importance of lifelong learning in enabling more people, not just the registered unemployed, who are out of the labour force to move back into employment, or even into employment for the first time. However, there is very little reliable evidence

European countries (EU-27 and six countries) using exploratory data analysis methods, linear regression models and cluster analysis with the goal of both discovering dependence of life-long learning on certain economic variables, and making cross-country comparisons, focusing on clusters of similar

and disadvantages that some groups of people face. Analysis and observation, documentation, statistics based on questionnaires and references are used in this research. In this respect the paper is focused on: • Investigations regarding the understanding of the lifelong learning concept; • Analyzing the resources

for the design of systems which implement lifelong user models. We conclude with discussion of broad issues that follow from our analysis, proposing a roadmap for research needed to achieve lifelong user models. 1

A key goal of AI is to create lifelong learn-ing agents that can leverage prior experience to improve performance on later tasks. In reinforcement-learning problems, one way to summarize prior experience for future use is through options, which are temporally extended actions (subpolicies) for how