to our expectations, we found that increasing teamwork in DCEE algorithms may lower team performance. In contrast, agents running DCOP algorithms improve their reward as teamwork increases. We term this previously unknown phenomenon the team uncertainty penalty, analyze it in both simulation and on robots, and present techniques to ameliorate the penalty.

This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved.

Mobile radiation detector systems aim to help identify dangerous sources of radiation while minimizing frequency of false alarms caused by non-threatening nuisance sources prevalent in cluttered urban scenes. We develop methods for spatially aggregating evidence from multiple spectral observations to simultaneously detect and infer properties of threatening radiation sources. Our Bayesian Aggregation (BA) framework allows sensor fusion across multiple measurements to boost detection capability of a radioactive point source, providing several key innovations previously unexplored in the literature. Our method learns the expected Signal-to-Noise Ratio (SNR) trend as a function of source exposure using Bayesian nonparametrics to enable robust detection. The method scales well in spatial search by leveraging conditional independence and locality in Bayesian updates. The framework also allows modeling of source parameters such as intensity or type to enable property characterization of detected sources. Approaches for incorporating modeling information into BA are compared and benchmarked with respect to other data fusion techniques.

All rights reserved 1 2 3 4 14 13 12 11 This volume is a product of the staff of the International Bank for Reconstruction and Development / The World Bank. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgement on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.

and the Philippines BALS Bureau of Alternative Learning Systems BPO business, process, and outsourcing CBT competency-based TVET CEO chief executive officer CHED Commission on Higher Education COE Center of Excellence CSI Commission of Supervised Institutions DTS dual-training system ER employment rate FDI foreign direct investment FIES Family Income and Expenditure Survey GCI Global Competitiveness Index GDP gross domestic product GER gross enrollment rate HEI higher education institution HR human resources Abbreviations• Technical (or job-specific) skills: skills associated with one's profession, generally a mix of specific knowledge and skills to perform jobs Skills acquisition is a complex process. While the book focuses on education and training, it is important to acknowledge that skills are produced in many different ways: preemployment education and training (formal and informal), on-the-job training (formal and informal), work and life experience, and learning from peers at school and work. Skills acquisition is fundamentally a cumulative dynamic process starting at birth with parental education and continuing through school education, training, and experience. While skills can grow over time, they can, however, also deteriorate if possibilities for lifelong learning are not well developed. Addi tionally, a share of the population can be excluded from effective skills acquisition if alternative "second-chance" skills development pathways do not exist for vulnerable youth.Road map of the book. Part I of the book investigates trends in demand for skills in the country overall and by sectors, explores its possible determinants, and attempts to identify emerging skills gaps. Part II turns to the analysis of the supply of skills in the country with a focus on the ability of education and training to provide highly skilled labor, keeping workers' skills updated, and providing skills development opportunities for the unskilled. It explores employers' perceptions on the quality of institutions and provides detailed analysis of the main characteristics, outcomes, and challenges in four key (or growing) subsectors of the provision of skills in the country: higher education, postsecondary technical-vocational education, nonformal secondary education, and postemployment training. It concludes with a summary of policy recommendations. Trends and Drivers of Demand for SkillsSkills demand has been growing and changing in the Philippines related to changes in output and employment structure (across and within sectors), openness to new technology, and pressures of international competition. An overall storyline emerges from this study. The Philippines workforce has become increasingly educated over these last 20 years, while at the same time the demand for education has been growing overall-as illustrated by an increase in the education wage premium (figure O.2)-and changing with a focus on the service sector. To the extent that education can be taken as an indirect measure of intermediate and advanced skills (academic, ...