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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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Military drones have recently been hailed as a revolutionary new technology that will forever change the conduct of war. And yet the United States and other countries have been deploying such unmanned military systems for more than a century. Written by a renowned authority in the field, this book documents the forgotten legacy of these pioneering efforts, offering the first comprehensive historical and technical accounting of unmanned air, land, sea, and underwater systems. Focusing on examples introduced during the two world wars, H. R.

In Adversarial Design, Carl DiSalvo examines the ways that technology design can provoke and engage the political. He describes a practice, which he terms “adversarial design,” that uses the means and forms of design to challenge beliefs, values, and what is taken to be fact. It is not simply applying design to politics—attempting to improve governance for example, by redesigning ballots and polling places; it is implicitly contestational and strives to question conventional approaches to political issues.

Attention in the Age of Embodied Information

The world is filling with ever more kinds of media, in ever more contexts and formats. Glowing rectangles have become part of the scene; screens, large and small, appear everywhere. Physical locations are increasingly tagged and digitally augmented. Amid this flood, your attention practices matter more than ever. You might not be able to tune this world out. So it is worth remembering that underneath all these augmentations and data flows, fixed forms persist, and that to notice them can improve other sensibilities.

With robots, we are inventing a new species that is part material and part digital. The ambition of modern robotics goes beyond copying humans, beyond the effort to make walking, talking androids that are indistinguishable from people. Future robots will have superhuman abilities in both the physical and digital realms. They will be embedded in our physical spaces, with the ability to go where we cannot, and will have minds of their own, thanks to artificial intelligence.

The Fourth Great Scientific Domain

Computing is not simply about hardware or software, or calculation or applications. Computing, writes Paul Rosenbloom, is an exciting and diverse, yet remarkably coherent, scientific enterprise that is highly multidisciplinary yet maintains a unique core of its own. In On Computing, Rosenbloom proposes that computing is a great scientific domain on a par with the physical, life, and social sciences.

The idea that human history is approaching a “singularity”—that ordinary humans will someday be overtaken by artificially intelligent machines or cognitively enhanced biological intelligence, or both—has moved from the realm of science fiction to serious debate. Some singularity theorists predict that if the field of artificial intelligence (AI) continues to develop at its current dizzying rate, the singularity could come about in the middle of the present century.

Algorithms, Worked Examples, and Case Studies

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Theory and Application

Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective.

The field of Artificial Life (ALife) is now firmly established in the scientific world, but it has yet to achieve one of its original goals: an understanding of the emergence of life on Earth. The new field of Artificial Chemistries draws from chemistry, biology, computer science, mathematics, and other disciplines to work toward that goal. For if, as it has been argued, life emerged from primitive, prebiotic forms of self-organization, then studying models of chemical reaction systems could bring ALife closer to understanding the origins of life.

The Little Prover introduces inductive proofs as a way to determine facts about computer programs. It is written in an approachable, engaging style of question-and-answer, with the characteristic humor of The Little Schemer (fourth edition, MIT Press). Sometimes the best way to learn something is to sit down and do it; the book takes readers through step-by-step examples showing how to write inductive proofs.

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