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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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Technology for Well-Being and Human Potential

On the eve of Google’s IPO in 2004, Larry Page and Sergey Brin vowed not to be evil. Today, a growing number of technologists would go further, trying to ensure that their work actively improves people’s lives. Technology, so pervasive and ubiquitous, has the capacity to increase stress and suffering; but it also has the less-heralded potential to improve the well-being of individuals, society, and the planet.

A Primer

This book offers a concise and accessible introduction to the emerging field of artificial cognitive systems. Cognition, both natural and artificial, is about anticipating the need for action and developing the capacity to predict the outcome of those actions. Drawing on artificial intelligence, developmental psychology, and cognitive neuroscience, the field of artificial cognitive systems has as its ultimate goal the creation of computer-based systems that can interact with humans and serve society in a variety of ways.

Category theory was invented in the 1940s to unify and synthesize different areas in mathematics, and it has proven remarkably successful in enabling powerful communication between disparate fields and subfields within mathematics. This book shows that category theory can be useful outside of mathematics as a rigorous, flexible, and coherent modeling language throughout the sciences.

Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and computer vision.

Basics and Extensions

Spreadsheets are used daily by millions of people for tasks that range from organizing a list of addresses to carrying out complex economic simulations. Spreadsheet programs are easy to learn and convenient to use because they have a clear visual model and a simple efficient underlying computational model. Yet although the basic spreadsheet model could be extended, improved, or otherwise experimented with in many ways, there is no coherently designed, reasonably efficient open source spreadsheet implementation that is a suitable platform for such experiments.

A Gentle Introduction

The combination of two of the twentieth century’s most influential and revolutionary scientific theories, information theory and quantum mechanics, gave rise to a radically new view of computing and information. Quantum information processing explores the implications of using quantum mechanics instead of classical mechanics to model information and its processing. Quantum computing is not about changing the physical substrate on which computation is done from classical to quantum but about changing the notion of computation itself, at the most basic level.

Voyages of Scientific Discovery with the Mars Exploration Rovers

Geologists in the field climb hills and hang onto craggy outcrops; they put their fingers in sand and scratch, smell, and even taste rocks. Beginning in 2004, however, a team of geologists and other planetary scientists did field science in a dark room in Pasadena, exploring Mars from NASA’s Jet Propulsion Laboratory (JPL) by means of the remotely operated Mars Exploration Rovers (MER).

Complex communicating computer systems—computers connected by data networks and in constant communication with their environments—do not always behave as expected. This book introduces behavioral modeling, a rigorous approach to behavioral specification and verification of concurrent and distributed systems. It is among the very few techniques capable of modeling systems interaction at a level of abstraction sufficient for the interaction to be understood and analyzed.

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts.

All design is situated—carried out from an embedded position. Design involves many participants and encompasses a range of interactions and interdependencies among designers, designs, design methods, and users. Design is also multidisciplinary, extending beyond the traditional design professions into such domains as health, culture, education, and transportation. This book presents eighteen situated design methods, offering cases and analyses of projects that range from designing interactive installations, urban spaces, and environmental systems to understanding customer experiences.

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