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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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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.

The Mathematical Foundations of Music

“Mathematics can be as effortless as humming a tune, if you know the tune,” writes Gareth Loy. In Musimathics, Loy teaches us the tune, providing a friendly and spirited tour of the mathematics of music—a commonsense, self-contained introduction for the nonspecialist reader. It is designed for musicians who find their art increasingly mediated by technology, and for anyone who is interested in the intersection of art and science.

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.

Adaptivity and Search in Evolving Neural Systems

Emergence—the formation of global patterns from solely local interactions—is a frequent and fascinating theme in the scientific literature both popular and academic. In this book, Keith Downing undertakes a systematic investigation of the widespread (if often vague) claim that intelligence is an emergent phenomenon. Downing focuses on neural networks, both natural and artificial, and how their adaptability in three time frames—phylogenetic (evolutionary), ontogenetic (developmental), and epigenetic (lifetime learning)—underlie the emergence of cognition.

Experiments in Cooperative Cognitive Architecture

In this book, Whitman Richards offers a novel and provocative proposal for understanding decision making and human behavior. Building on Valentino Braitenberg’s famous “vehicles,” Richards describes a collection of mental organisms that he calls “daemons”—virtual correlates of neural modules. Daemons have favored choices and make decisions that control behaviors of the group to which they belong, with each daemon preferring a different outcome. Richards arranges these preferences in graphs, linking similar choices, which thus reinforce each other.

Algorithms and Applications

Our increasingly integrated world relies on networks both physical and virtual to transfer goods and information. The Internet is a network of networks that connects people around the world in a real-time manner, but it can be disrupted by massive data flows, diverse traffic patterns, inadequate infrastructure, and even natural disasters and political conflict. Similar challenges exist for transportation and energy distribution networks.

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