Jorg P. Muller – författare

The Department of Veterans Affairs (VA) provides a range of benefits and services to veterans and eligible dependents who meet certain criteria as authorized by law. These benefits include medical care, disability compensation and pensions, education, vocational rehabilitation and employment services, assistance to homeless veterans, home loan guarantees, administration of life insurance and traumatic injury protection insurance for service members, and death benefits that cover burial expenses. Chapter 1 focuses on FY2018 appropriations and FY2019 advance appropriations for the Department of Veterans Affairs (VA). VA is one of the Federal government’s largest property holding entities with a capital asset portfolio that includes thousands of medical facilities spanning hundreds of millions of square feet in both owned and leased space across the country. The average VA medical facility building is five times older than the average building in a not for profit hospital system. All too often current facilities, including those that have been well maintained, are not equipped to support the provisions of modern high quality care and are not well suited to providing care in the current VA healthcare system. As reported in chapter 2, there is a wide and growing gap between VA’s capital need and the antiquated and anticipated resources. Following the brief legislative history of VA provided community care, chapter 3 describes the background and legislative history leading up to the enactment of the VA MISSION Act. This is followed by summaries of the major provisions in the VA MISSION Act by title. The chapter concludes with an appendix providing implementation and reporting deadlines contained in the VA MISSION Act. VHA anticipates that it will provide care to more than 7 million veterans in fiscal year 2019. The majority of veterans using VHA health care services receive care in one or more of the 172 medical centers or at associated outpatient facilities. Chapter 4 assesses VHA’s management of medical center performance. Chapter 5 reviews the new rule entitled “VA Claims and Appeals Modernization” (RIN: 2900-AQ26), which amends the regulations governing claims adjudication and appeals. VBA employees have authority to request reexaminations for veterans “whenever VA determines there is a need to verify either the continued existence or the current severity of a disability,” and when there is no exclusion from reexamination. Chapter 6 determines whether Veterans Benefits Administration (VBA) employees required disabled veterans to submit to unwarranted medical reexaminations. Training health care professionals is part of the VA’s statutory mission. The VA is the largest provider of medical training in the United States and is involved in training at all levels: medical students, medical residents, and medical fellows Chapter 7 focuses on physician training.

This book constitutes revised selected papers from the 13th International Workshop on Engineering Multi-Agent Systems, EMAS 2025, which took place in Detroit, USA, during May 19–20, 2025.The 13 full papers in this book were carefully reviewed and selected from a total of 16 submissions. The book also contains one paper on the community roadmap for EMAS. The contributions focus on topics such as agent-oriented software engineering, programming multi-agent systems, declarative agent languages and technologies, artificial intelligence, and machine learning.

This book constitutes the proceedings of the 12th German Conference on Multiagent System Technologies, MATES 2014, held in Stuttgart, Germany, in September 2014. The 9 full papers and 7 short papers included in this volume were carefully reviewed and selected from 31 submissions. The book also contains 2 invited talks. The papers are organized in topical sections named: mechanisms, negotiation, and game theory; multiagent planning, learning, and control; and multiagent systems engineering, modeling and simulation.

The work on Autonomic Road Transport Support (ARTS) presented here aims at meeting the challenge of engineering autonomic behavior in Intelligent Transportation Systems (ITS) by fusing research from the disciplines of traffic engineering and autonomic computing. Ideas and techniques from leading edge artificial intelligence research have been adapted for ITS over the last 30 years. Examples include adaptive control embedded in real time traffic control systems, heuristic algorithms (e.g. in SAT-NAV systems), image processing and computer vision (e.g. in automated surveillance interpretation). Autonomic computing which is inspired from the biological example of the body’s autonomic nervous system is a more recent development. It allows for a more efficient management of heterogeneous distributed computing systems. In the area of computing, autonomic systems are endowed with a number of properties that are generally referred to as self-X properties, including self-configuration, self-healing, self-optimization, self-protection and more generally self-management. Some isolated examples of autonomic properties such as self-adaptation have found their way into ITS technology and have already proved beneficial.   This edited volume provides a comprehensive introduction to Autonomic Road Transport Support (ARTS) and describes the development of ARTS systems. It starts out with the visions, opportunities and challenges, then presents the foundations of ARTS and the platforms and methods used and it closes with experiences from real-world applications and prototypes of emerging applications. This makes it suitable for researchers and practitioners in the fields of autonomic computing, traffic and transport management and engineering, AI, and software engineering. Graduate students will benefit from state-of-the-art description, the study of novel methods and the case studies provided.

This book constitutes the proceedings of the 13th German Conference on Multiagent System Technologies, MATES 2015, held in Cottbus, Germany, in September 2015.The 11 full papers papers presented together with 2 short papers, 1 invited paper and 4 extended abstracts of doctoral papers in this volume were carefully reviewed and selected from 27 submissions. The papers are organized in topical sections on MAS engineering, modeling, and simulation; smart things working together; and innovative and emerging applications of MAS.