Revival Twelfth International Conference On Adaptive Structures And Technologies 2002
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Reinforcement Learning
Author: Richard S. Sutton
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. These two characteristics -- trial-and-error search and delayed reward -- are the most important distinguishing features of reinforcement learning. Reinforcement learning is both a new and a very old topic in AI. The term appears to have been coined by Minsk (1961), and independently in control theory by Walz and Fu (1965). The earliest machine learning research now viewed as directly relevant was Samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. Of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the AI/engineering work. One could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). Reinforcement Learning is an edited volume of original research, comprising seven invited contributions by leading researchers.
Digital Governance
The application of digital information and communication technologies (ICTs) to reform governmental structures and public service is widely and perhaps naively viewed as the 21st century "savior", the enlightened way to reinvigorate democracy, reduce costs, and improve the quality of public services. This book examines the transition from e-government to digital governance in light of the financial exigencies and political controversies facing many governments. The chapters concentrate on strategies for public sector organizational transformation and policies for improved and measurable government performance in the current contentious political environment. This fully updated second edition of Digital Governance provides strategies for public officials to apply advanced technologies, manage remote workforces, measure performance, and improve service delivery in current crisis-driven administrative and political environments. The full implementation of advanced digital governance requires fundamental changes in the relationship between citizens and their governments, using ICTs as catalysts for political as well as administrative communication. This entails attitudinal and behavioral changes, secure networks, and less dependence on formal bureaucratic structures (covered in Part I of this book); transformation of administrative, educational, and security systems to manage public services in a more citizen-centric way (covered in Part II); the integration of advanced digital technologies with remote broadband wireless internet services (Part III); and the creation of new forms of global interactive citizenship and self-governance (covered in Part IV). Author Michael E. Milakovich offers recommendations for further improvement and civic actions to stimulate important instruments of governance and public administration. This book is required reading for political science, public administration, and public policy courses, as well as federal, state, and local government officials.
Water Societies and Technologies from the Past and Present
Today our societies face great challenges with water, in terms of both quantity and quality, but many of these challenges have already existed in the past. Focusing on Asia, Water Societies and Technologies from the Past and Present seeks to highlight the issues that emerge or re-emerge across different societies and periods, and asks what they can tell us about water sustainability. Incorporating cutting-edge research and pioneering field surveys on past and present water management practices, the interdisciplinary contributors together identify how societies managed water resource challenges and utilised water in ways that allowed them to evolve, persist, or drastically alter their environment. The case studies, from different periods, ancient and modern, and from different regions, including Egypt, Sri Lanka, Cambodia, Southwest United States, the Indus Basin, the Yangtze River, the Mesopotamian floodplain, the early Islamic city of Sultan Kala in Turkmenistan, and ancient Korea, offer crucial empirical data to readers interested in comparing the dynamics of water management practices across time and space, and to those who wish to understand water-related issues through conceptual and quantitative models of water use. The case studies also challenge classical theories on water management and social evolution, examine and establish the deep historical roots and ecological foundations of water sustainability issues, and contribute new grounds for innovations in sustainable urban planning and ecological resilience.