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Bayesian Artificial Intelligence
The second edition of this bestseller provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. This edition contains a new chapter on Bayesian network classifiers and a new section on object-oriented Bayesian networks, along with new applications and case studies. It includes a new section that addresses foundational problems with causal discovery and Markov blanket discovery and a new section that covers methods of evaluating causal discovery programs. The book also offers more coverage on the uses of causal interventions to understand and reason with causal Bayesian networks. Supplemental materials are available on the book's website.
Bayesian Artificial Intelligence
As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors’ website.
Bayesian Artificial Intelligence, Second Edition
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology. New to the Second Edition New chapter on Bayesian network classifiers New section on object-oriented Bayesian networks New section that addresses foundational problems with causal discovery and Ma...
New Technology and Curriculum Design
Fifth in the 'NCELTR Teacher Resource' series, this book documents a project investigating the impact of new technology on three aspects of distance learning: the course design process, learners' interaction with course materials and teachers' interaction with learners and materials. Relevant to teachers of ESL and other languages through distance education programs. Margaret Anderton and Ann Nicholson are currently working in Distance Learning within AMES WA. Liz Bailey has worked in the adult ESL area as a teacher and coordinator.
Evolving Ethics
This book describes the application of Artificial Life simulation to evolutionary scenarios of wide ethical interest, including the evolution of altruism, rape and abortion, providing a new meaning to "experimental philosophy". The authors also apply evolutionary ALife techniques to explore contentious issues within evolutionary theory itself, such as the evolution of aging. They justify these uses of simulation in science and philosophy, both in general and in their specific applications here. Evolving Ethics will be of interest to researchers, enthusiasts, students and interested lay readers in the fields of Artificial Life, philosophy of science, ethics, agent- and individual-based modeling in ecology and the social sciences, computer simulation, evolutionary biology, evolutionary psychology and the social sciences.
Upstaged
First Published in 2006. Routledge is an imprint of Taylor & Francis, an informa company.
Innovations in Bayesian Networks
Bayesian networks currently provide one of the most rapidly growing areas of research in computer science and statistics. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. Each of the twelve chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Graduate students since it shows the direction of current research.
Global Health
The concept of global health has moved on from focusing on the problems of the developing world to encompass health problems with global impact. Global health issues impact daily on local healthcare delivery and professional practice. This illuminating guide for healthcare students and practitioners introduces the major themes, challenges and debates relevant to global health that will equip the reader with the knowledge and skills required to thrive in this multi-faceted area of practice. Key features Puts global health in context considering key issues including health inequalities, human health and the global environment and climate change. Ideal reading for international electives, voluntary work, and further qualifications in global health. Contains insights from leading experts in the field. Relevant to those working in a culturally diverse context whether domestic or international.
