A radical and challenging book which argues that artificial intelligence needs a completely different set of foundations, based on ecological intelligence rather than human intelligence, if it is to deliver on the promise of a better world. This can usher in the greatest transformation in human history, an age of re-integration. Our very existence is dependent upon our context within the Earth System, and so, surely, artificial intelligence must also be grounded within this context, embracing emergence, interconnectedness and real-time feedback. We discover many positive outcomes across the societal, economic and environmental arenas and discuss how this transformation can be delivered. Key Features: Identifies a key weakness in current AI thinking, that threatens any hope of a better world. Highlights the importance of realizing that systems theory is an essential foundation for any technology that hopes to positively transform our world. Emphasizes the need for a radical new approach to AI, based on ecological systems. Explains why ecosystem intelligence, not human intelligence, offers the best framework for AI. Examines how this new approach will impact on the three arenas of society, environment and economics, ushering in a new age of re-integration.
Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4.
Stories of environmental stewardship in communities from New Orleans to Soweto accompany an interdisciplinary framework for understanding civic ecology as a global phenomenon. In communities across the country and around the world, people are coming together to rebuild and restore local environments that have been affected by crisis or disaster. In New Orleans after Katrina, in New York after Sandy, in Soweto after apartheid, and in any number of postindustrial, depopulated cities, people work together to restore nature, renew communities, and heal themselves. In Civic Ecology, Marianne Krasny and Keith Tidball offer stories of this emerging grassroots environmental stewardship, along with an interdisciplinary framework for understanding and studying it as a growing international phenomenon. Krasny and Tidball draw on research in social capital and collective efficacy, ecosystem services, social learning, governance, social-ecological systems, and other findings in the social and ecological sciences to investigate how people, practices, and communities interact. Along the way, they chronicle local environmental stewards who have undertaken such tasks as beautifying blocks in the Bronx, clearing trash from the Iranian countryside, and working with traumatized veterans to conserve nature and recreate community. Krasny and Tidball argue that humans' innate love of nature and attachment to place compels them to restore nature and places that are threatened, destroyed, or lost. At the same time, they report, nature and community exert a healing and restorative power on their stewards.
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