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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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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.

A cyber-physical system consists of a collection of computing devices communicating with one another and interacting with the physical world via sensors and actuators in a feedback loop. Increasingly, such systems are everywhere, from smart buildings to medical devices to automobiles. This textbook offers a rigorous and comprehensive introduction to the principles of design, specification, modeling, and analysis of cyber-physical systems.

The dominant feature of modern technology is not how productive it makes us, or how it has revolutionized the workplace, but how enjoyable it is. We take pleasure in our devices, from smartphones to personal computers to televisions. Whole classes of leisure activities rely on technology. How has technology become such an integral part of enjoyment?

Modeling Natural, Social, and Engineered Complex Systems with NetLogo

The advent of widespread fast computing has enabled us to work on more complex problems and to build and analyze more complex models. This book provides an introduction to one of the primary methodologies for research in this new field of knowledge. Agent-based modeling (ABM) offers a new way of doing science: by conducting computer-based experiments. ABM is applicable to complex systems embedded in natural, social, and engineered contexts, across domains that range from engineering to ecology.

We turn on the lights in our house from a desk in an office miles away. Our refrigerator alerts us to buy milk on the way home. A package of cookies on the supermarket shelf suggests that we buy it, based on past purchases. The cookies themselves are on the shelf because of a “smart” supply chain. When we get home, the thermostat has already adjusted the temperature so that it’s toasty or bracing, whichever we prefer. This is the Internet of Things—a networked world of connected devices, objects, and people.

The Story of India's IT Revolution

The rise of the Indian information technology industry is a remarkable economic success story. Software and services exports from India amounted to less than $100 million in 1990, and today come close to $100 billion. But, as Dinesh Sharma explains in The Outsourcer, Indian IT’s success has a long prehistory; it did not begin with software support, or with American firms’ eager recruitment of cheap and plentiful programming labor, or with India’s economic liberalization of the 1990s.

Stanford and the Computer Music Revolution

In the 1960s, a team of Stanford musicians, engineers, computer scientists, and psychologists used computing in an entirely novel way: to produce and manipulate sound and create the sonic basis of new musical compositions. This group of interdisciplinary researchers at the nascent Center for Computer Research in Music and Acoustics (CCRMA, pronounced “karma”) helped to develop computer music as an academic field, invent the technologies that underlie it, and usher in the age of digital music.

The vast differences between the brain’s neural circuitry and a computer’s silicon circuitry might suggest that they have nothing in common. In fact, as Dana Ballard argues in this book, computational tools are essential for understanding brain function. Ballard shows that the hierarchical organization of the brain has many parallels with the hierarchical organization of computing; as in silicon computing, the complexities of brain computation can be dramatically simplified when its computation is factored into different levels of abstraction.

We now know that there is much more to classical mechanics than previously suspected. Derivations of the equations of motion, the focus of traditional presentations of mechanics, are just the beginning. This innovative textbook, now in its second edition, concentrates on developing general methods for studying the behavior of classical systems, whether or not they have a symbolic solution. It focuses on the phenomenon of motion and makes extensive use of computer simulation in its explorations of the topic.

Turing, Gödel, Church, and Beyond

In the 1930s a series of seminal works published by Alan Turing, Kurt Gödel, Alonzo Church, and others established the theoretical basis for computability. This work, advancing precise characterizations of effective, algorithmic computability, was the culmination of intensive investigations into the foundations of mathematics. In the decades since, the theory of computability has moved to the center of discussions in philosophy, computer science, and cognitive science.

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