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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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Each of us has an ever-growing collection of personal digital data: documents, photographs, PowerPoint presentations, videos, music, emails and texts sent and received. To access any of this, we have to find it. The ease (or difficulty) of finding something depends on how we organize our digital stuff. In this book, personal information management (PIM) experts Ofer Bergman and Steve Whittaker explain why we organize our personal digital data the way we do and how the design of new PIM systems can help us manage our collections more efficiently.

Edited by Gerhard Weiss

Multiagent systems are made up of multiple interacting intelligent agents—computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care.

The Palladio Approach

Too often, software designers lack an understanding of the effect of design decisions on such quality attributes as performance and reliability. This necessitates costly trial-and-error testing cycles, delaying or complicating rollout. This book presents a new, quantitative architecture simulation approach to software design, which allows software engineers to model quality of service in early design stages.

Robots are entering the mainstream. Technologies have advanced to the point of mass commercialization—Roomba, for example—and adoption by governments—most notably, their use of drones. Meanwhile, these devices are being received by a public whose main sources of information about robots are the fantasies of popular culture. We know a lot about C-3PO and Robocop but not much about Atlas, Motoman, Kiva, or Beam—real-life robots that are reinventing warfare, the industrial workplace, and collaboration.

The New AI

Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don’t yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data.

66 Ways Experts Think

“This is the book I wish I’d had around throughout my journey as a software architect. It’s charming, approachable, and full of wisdom—you’ll learn things you'll come back to again and again.”
Grady Booch, IBM Fellow and Chief Scientist, IBM

Intelligent Cars and the Road Ahead

“Smart, wide-ranging, [and] nontechnical.”
—Los Angeles Times

“Anyone who wants to understand what's coming must read this fascinating book.”
Martin Ford, New York Times bestselling author of Rise of the Robots

With Application to Understanding Data

This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data.

Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C “actually caused” event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established in order to determine responsibility. The philosophy literature has been struggling with the problem of defining causality since Hume.

Biosensing Technologies in Everyday Life
Edited by Dawn Nafus

Today anyone can purchase technology that can track, quantify, and measure the body and its environment. Wearable or portable sensors detect heart rates, glucose levels, steps taken, water quality, genomes, and microbiomes, and turn them into electronic data. Is this phenomenon empowering, or a new form of social control? Who volunteers to enumerate bodily experiences, and who is forced to do so? Who interprets the resulting data? How does all this affect the relationship between medical practice and self care, between scientific and lay knowledge?

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