Education and Training Funded by the H-1B Visa Fee and the Demand for Information Technology and Other Professional Specialty Workers

CRS_April_2005_Education_and_Training_Funded_by_the_H_1B.pdf: 1087 downloads, before Oct. 1, 2020

Self-Employment as a Contributor to Job Growth and as an Alternative Work Arrangement

CRS_September_2004_Self_Employment_as_a_Contributor_to_Job_Growth.pdf: 560 downloads, before Oct. 1, 2020

Youth: From Classroom to Workplace?

Much attention has been devoted to the implications of the aging of the U.S. population for the future supply of labor to the nation’s employers, but little of the discourse about remedies has addressed the younger members of the working-age population. This paper examines issues such as whether the youngest replacements for retiring baby-boomers are being fully utilized in the sense that most teenagers and young adults successfully transition from the classroom to the workplace and which 16-24 year olds are, instead, more likely to impose costs on society rather than contribute to the economy as taxpayers. In addition, the report identifies risk factors for out-of-school and out-of work youth including characteristics of the neighborhoods in which they live, the proximity of those neighborhoods to jobs, and the characteristics of their families. The report concludes that the results of empirical research suggest that a comprehensive youth employment policy would include training programs that provide, among other things, work experience to young students raised in poor inner-city neighborhoods; delinquency prevention measures, particularly for low-income children with incarcerated family and friends; changes to public transportation and to housing patterns to give at-risk youth greater access to areas of job growth; enhanced enforcement of employment and housing discrimination laws; and neighborhood workforce as well as community/economic development initiatives

A Policy Search Method For Temporal Logic Specified Reinforcement Learning Tasks

Reward engineering is an important aspect of reinforcement learning. Whether or not the user's intentions can be correctly encapsulated in the reward function can significantly impact the learning outcome. Current methods rely on manually crafted reward functions that often require parameter tuning to obtain the desired behavior. This operation can be expensive when exploration requires systems to interact with the physical world. In this paper, we explore the use of temporal logic (TL) to specify tasks in reinforcement learning. TL formula can be translated to a real-valued function that measures its level of satisfaction against a trajectory. We take advantage of this function and propose temporal logic policy search (TLPS), a model-free learning technique that finds a policy that satisfies the TL specification. A set of simulated experiments are conducted to evaluate the proposed approach

The Family and Medical Leave Act: Current Legislative Activity

[Excerpt] Congress passed the Family and Medical Leave Act (FMLA) as a means of helping individuals more easily balance their family and work obligations. Over the past few decades, married mothers with young children increasingly have strived to fulfill both workplace and child-rearing obligations. With the enactment of welfare reform legislation, greater numbers of single parents also have had to meet the challenge of caring for their children while holding down jobs. Further, the aging of the population and lengthening life spans have made it more likely that workers will assume caregiving duties for elderly relatives, friends, and neighbors. This report begins with a brief overview of the major features of the FMLA and its regulations. The various proposals made to amend the act since its inception are then categorized and discussed. It closes with a review of legislative activity