Artificial Intelligence and Molecular Biology
by Lawrence Hunter
Publisher: AAAI Press 1993
Number of pages: 467
These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book.
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by Bill Hibbard - arXiv
This book analyzes the issues of ethical artificial intelligence. The behavior of future AI systems can be described by mathematical equations, which are adapted to analyze possible unintended AI behaviors and ways that AI designs can avoid them.
by Mike Sharples, et al. - A Bradford Book
The aim of this book is to introduce people with little or no computing background to artificial intelligence (AI) and cognitive science. It emphasizes the psychological, social, and philosophical implications of artificial intelligence.
by George K Matsopoulos - InTech
Contents: Learning the Number of Clusters in Self Organizing Map; Neural-Network Enhanced Visualization of High-Dimensional Data; SOM-based Applications in Remote Sensing; Segmentation of Satellite Images Using SOM; Face Recognition Using SOM; etc.
by David Moursund - University of Oregon
This book is designed to help teachers learn about the educational implications of current uses of Artificial Intelligence as an aid to solving problems and accomplishing tasks. The text is designed for self-study or for use in workshops.