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The Quest for Artificial Intelligence
Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
Neural Nets
This book constitutes the thoroughly refereed post-proceedings of the 13th Italian Workshop on Neural Nets, WIRN VIETRI 2002, held in Vietri sul Mare, Italy in May/June 2002.The 21 revised full papers presented together with three invited papers were carefully reviewed and revised during two rounds of selection and improvement. The papers are organized in topical sections on architectures and algorithms, image and signal processing applications, and learning in neural networks.
Biology And Computation: A Physicist's Choice
This book provides a comprehensive review of the works in the rapidly evolving field of neural networks and brain studies. Its purpose is two-fold: to help physicists entering this field to get a broader view of the context of the domain, and to help scientists of other disciplines to reach a better understanding of the physicists' contributions within a context of perspectives they can relate to.Included in the volume are 68 carefully selected, high quality reprints to provide the volume with both breadth and depth. It is organized into 5 sections and 22 chapters, both the sections and chapters being preceded by introductory comments by the editors.
Mosaic
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ECAI 2016
Artificial Intelligence continues to be one of the most exciting and fast-developing fields of computer science. This book presents the 177 long papers and 123 short papers accepted for ECAI 2016, the latest edition of the biennial European Conference on Artificial Intelligence, Europe’s premier venue for presenting scientific results in AI. The conference was held in The Hague, the Netherlands, from August 29 to September 2, 2016. ECAI 2016 also incorporated the conference on Prestigious Applications of Intelligent Systems (PAIS) 2016, and the Starting AI Researcher Symposium (STAIRS). The papers from PAIS are included in this volume; the papers from STAIRS are published in a separate volume in the Frontiers in Artificial Intelligence and Applications (FAIA) series. Organized by the European Association for Artificial Intelligence (EurAI) and the Benelux Association for Artificial Intelligence (BNVKI), the ECAI conference provides an opportunity for researchers to present and hear about the very best research in contemporary AI. This proceedings will be of interest to all those seeking an overview of the very latest innovations and developments in this field.
Multi-Objective Machine Learning
Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.
Dreamers, Visionaries, and Revolutionaries in the Life Sciences
What are the conditions that foster true novelty and allow visionaries to set their eyes on unknown horizons? What have been the challenges that have spawned new innovations, and how have they shaped modern biology? In Dreamers, Visionaries, and Revolutionaries in the Life Sciences, editors Oren Harman and Michael R. Dietrich explore these questions through the lives of eighteen exemplary biologists who had grand and often radical ideas that went far beyond the run-of-the-mill science of their peers. From the Frenchman Jean-Baptiste Lamarck, who coined the word “biology” in the early nineteenth century, to the American James Lovelock, for whom the Earth is a living, breathing organism, t...
