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Imagine living in 1958, and knowing that the integrated circuit--the microchip--was about to be invented, and would revolutionize the world. Or imagine 1992, when the Internet was about to transform virtually every aspect of our lives. Incredibly, this book argues that we stand at such a moment right now--and not just in one field, but in many. In 2030, authors Rutger van Santen, Djan Khoe, and Bram Vermeer interview over two dozen scientific and technological experts on themes of health, sustainability and communication, asking them to look forward to the year 2030 and comment on the kind of research that will play a necessary role. If we know what technology will be imperative in 2030, the authors reason, what can we do now to influence future breakthroughs? Despite working in dissimilar fields, the experts called upon in the book - including Hans Blix (Head of the UN investigation in Iraq), Craig Venter (explorer of the human DNA), and Susan Greenfield (a leading world authority on the human brain), among many others - all emphasize the interconnectedness of our global networks in technology and communication, so tightly knit that the world's major conflicts are never isolated incidents. A fresh understanding of the regularities underlying these complex systems is more important than ever. Using bright, accessible language to discuss topics of universal interest and relevance, 2030 takes the position that we can, in fact, influence the course of history. It offers a new way of looking forward, a fresh perspective on sustainability, stability and crisis-prevention. For anyone interested in modern science, this book will showcase the technologies that will soon change the way we live.

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. In this book, Joseph Halpern explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression. Halpern applies and expands an approach to causality that he and Judea Pearl developed, based on structural equations. He carefully formulates a definition of causality, and building on this, defines degree of responsibility, degree of blame, and causal explanation. He concludes by discussing how these ideas can be applied to such practical problems as accountability and program verification.

Robots may one day rule the world, but what is a robot-ruled Earth like? Many think the first truly smart robots will be brain emulations or ems. Scan a human brain, then run a model with the same connections on a fast computer, and you have a robot brain, but recognizably human. Train an em to do some job and copy it a million times: an army of workers is at your disposal. When they can be made cheaply, within perhaps a century, ems will displace humans in most jobs. In this new economic era, the world economy may double in size every few weeks. Some say we can't know the future, especially following such a disruptive new technology, but Professor Robin Hanson sets out to prove them wrong. Applying decades of expertise in physics, computer science, and economics, he uses standard theories to paint a detailed picture of a world dominated by ems. While human lives don't change greatly in the em era, em lives are as different from ours as our lives are from those of our farmer and forager ancestors. Ems make us question common assumptions of moral progress, because they reject many of the values we hold dear. Read about em mind speeds, body sizes, job training and career paths, energy use and cooling infrastructure, virtual reality, aging and retirement, death and immortality, security, wealth inequality, religion, teleportation, identity, cities, politics, law, war, status, friendship and love. This book shows you just how strange your descendants may be, though ems are no stranger than we would appear to our ancestors. To most ems, it seems good to be an em.

This highly topical text considers the construction of the next generation of the Web, called the Semantic Web. This will enable computers to automatically consume Web-based information, overcoming the human-centric focus of the Web as it stands at present, and expediting the construction of a whole new class of knowledge-based applications that will intelligently utilize Web content. The text is structured into three main sections on knowledge representation techniques, reasoning with multi-agent systems, and knowledge services. For each of these topics, the text provides an overview of the state-of-the-art techniques and the popular standards that have been defined. Numerous small programming examples are given, which demonstrate how the benefits of the Semantic Web technologies can be realized at the present time. The main theoretical results underlying each of the technologies are presented, and the main problems and research issues which remain are summarized. Based on a course on 'Multi-Agent Systems and the Semantic Web' taught at the University of Edinburgh, this text is ideal for final-year undergraduate and graduate students in Mathematics, Computer Science, Artificial Intelligence, and Logic and researchers interested in Multi-Agent Systems and the Semantic Web.

We live in an incredible period in history. The Computer Revolution may be even more life-changing than the Industrial Revolution. We can do things with computers that could never be done before, and computers can do things for us that could never be done before. But our love of computers should not cloud our thinking about their limitations. We are told that computers are smarter than humans and that data mining can identify previously unknown truths, or make discoveries that will revolutionize our lives. Our lives may well be changed, but not necessarily for the better. Computers are very good at discovering patterns, but are useless in judging whether the unearthed patterns are sensible because computers do not think the way humans think. We fear that super-intelligent machines will decide to protect themselves by enslaving or eliminating humans. But the real danger is not that computers are smarter than us, but that we think computers are smarter than us and, so, trust computers to make important decisions for us. The AI Delusion explains why we should not be intimidated into thinking that computers are infallible, that data-mining is knowledge discovery, and that black boxes should be trusted.

While many think of algorithms as specific to computer science, at its core algorithmic thinking is defined by the use of analytical logic to solve problems. This logic extends far beyond the realm of computer science and into the wide and entertaining world of puzzles. In Algorithmic Puzzles, Anany and Maria Levitin use many classic brainteasers as well as newer examples from job interviews with major corporations to show readers how to apply analytical thinking to solve puzzles requiring well-defined procedures. The book's unique collection of puzzles is supplemented with carefully developed tutorials on algorithm design strategies and analysis techniques intended to walk the reader step-by-step through the various approaches to algorithmic problem solving. Mastery of these strategies--exhaustive search, backtracking, and divide-and-conquer, among others--will aid the reader in solving not only the puzzles contained in this book, but also others encountered in interviews, puzzle collections, and throughout everyday life. Each of the 150 puzzles contains hints and solutions, along with commentary on the puzzle's origins and solution methods. The only book of its kind, Algorithmic Puzzles houses puzzles for all skill levels. Readers with only middle school mathematics will develop their algorithmic problem-solving skills through puzzles at the elementary level, while seasoned puzzle solvers will enjoy the challenge of thinking through more difficult puzzles.

This book examines new forms of nascent life that emerge through technical interactions within human-constructed environments—“machinic life”—in the sciences of cybernetics, artificial life, and artificial intelligence. With the development of such research initiatives as the evolution of digital organisms, computer immune systems, artificial protocells, evolutionary robotics, and swarm systems, it argues, machinic life has achieved a complexity and autonomy worthy of study in its own right. Drawing on the publications of scientists as well as a range of work in contemporary philosophy and cultural theory, but always with the primary focus on the “objects at hand”—the machines, programs, and processes that constitute machinic life—the book shows how they come about, how they operate, and how they are already changing. This understanding is a necessary first step, it further argues, that must precede speculation about the meaning and cultural implications of these new forms of life. Developing the concept of the “computational assemblage” (a machine and its associated discourse) as a framework to identify both resemblances and differences in form and function, the book offers a conceptual history of each of the three sciences. It considers the new theory of machines proposed by cybernetics from several perspectives, including Lacanian psychoanalysis and “machinic philosophy.” The book examines the history of the new science of artificial life and its relation to theories of evolution, emergence, and complex adaptive systems (as illustrated by a series of experiments carried out on various software platforms).

New technology has brought with it new tools for learning, and research has shown that the educational potential of video games resonates with scholars, teachers, and students alike. This book describes the largely untapped potential of mobile learning games—games played on such handheld devices as cell phones, Game Boys, and Sony PSPs—to make a substantial impact on learning. Examining mobile games from both educational and gaming perspectives, it argues that the strengths of the mobile platform—its portability, context sensitivity, connectivity, and ubiquity—make it ideal for learning games in elementary, secondary, university, and lifelong education. The book begins by exploring the past and present of education, educational technology, “edutainment,” and mobile games. It then offers a series of case studies of mobile educational games that have been developed and implemented in recent years. These games—either participatory (which require interaction with other players) or augmented reality (which augment the real world with virtual information)—can be produced at lower cost than PC or full-size console games. They use social dynamics and real-world context to enhance game play, can be integrated into the natural flow of instruction more easily than their big-screen counterparts, and can create compelling educational and engaging environments for learners. They are especially well suited for helping learners at every level develop twenty-first century skills, including the ability to tackle complex problems and acquire information in “just-in-time” fashion.

This book provides a unique examination of the software development process, arguing that discipline, still dominated by methods conceived in the framework of older technologies, must undergo a fundamental reexamination of its guiding principles in order for significant progress to take place. To gain fresh insights into how we ought to direct future research, the author begins with a search for first principles. The book begins with an exploration of the scientific foundations of computer technology, then examines design from the perspective of practitioners. The book also offers a critique of the methods employed in software development and an evaluation of an alternate paradigm that has been used successfully for 14 years. The concepts reviewed here comprise a set of core readings for understanding the research and development challenges that will confront computer technology in the 21st century and will be of great interest to computer science researchers and educators, graduate students, and software engineers.

Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes. Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation. Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.

The completion of the first draft of the human genome has led to an explosion of interest in genetics and molecular biology. The view of the genome as a network of interacting computational components is well-established, but researchers are now trying to reverse the analogy, by using living organisms to construct logic circuits. The potential applications for such technologies is huge, ranging from bio-sensors, through industrial applications to drug delivery and diagnostics. This book would be the first to deal with the implementation of this technology, describing several working experimental demonstrations using cells as components of logic circuits, building toward computers incorporating biological components in their functioning.

Most of the information available on cloud computing is either highly technical, with details that are irrelevant to non-technologists, or pure marketing hype, in which the cloud is simply used as a selling point. This book, however, explains the cloud from the user's viewpoint. The author explains what the cloud is, when to use it (and when not to), how to select a cloud service, how to integrate it with other technologies, and what the best practices are for using cloud computing. A simple and basic definition of cloud computing from the National Institute of Science and Technology is considered: a model enabling ubiquitous, convenient, on-demand access to a shared pool of configurable computing resources. Thus businesses, individuals and communities can harness information technology resources usually available only to large enterprises. This, as the author demonstrates, represents a paradigm shift for businesses and individuals alike. In additon, the book considers the contractual, legal, financial, security and risk related aspects of adopting and migrating to the cloud. Cloud patterns are examined in terms of five deployment models; and a cloud computing maturity model is derived to align the use of cloud computing with best practices.A unique aspect of the book is that it provides innovative constructs that affect the way cloud computing shall be viewed and used in the future. In particular, it addresses novel concepts for cloud computing: cloud cells, or specialist clouds for specific uses; the personal cloud; the cloud of things and services; and cloud service exchanges.

The American ENIAC is customarily regarded as the first electronic computer. In this fascinating volume, Jack Copeland rewrites the history of computer science, arguing that in reality Colossus--the giant computer built in Bletchley Park by the British secret service during World War II--predates ENIAC by two years. Until very recently, much about the Colossus machine was shrouded in secrecy, largely because the code-breaking algorithms employed during World War II remained in use by the British security services until a short time ago. Copeland has brought together memoirs of veterans of Bletchley Park--the top-secret headquarters of Britain's secret service--and others who draw on the wealth of declassified information to illuminate the crucial role Colossus played during World War II. A must read for anyone curious about code-breaking or World War II espionage, Colossus offers a fascinating insider's account of the world's first giant computer, the great-great-grandfather of the massive computers used today by the CIA and the National Security Agency.

Currently there is growing interest in the application of dynamical methods to the study of cognition. Computation, Dynamics, and Cognition investigates this convergence from a theoretical and philosophical perspective, generating a provocative new view of the aims and methods of cognitive science. Advancing the dynamical approach as the methodological frame best equipped to guide inquiry in the field's two main research programs--the symbolic and connectionist approaches--Marco Giunti engages a host of questions crucial not only to the science of cognition, but also to computation theory, dynamical systems theory, philosophy of mind, and philosophy of science. In chapter one Giunti employs a dynamical viewpoint to explore foundational issues in computation theory. Using the concept of Turing computability, he precisely and originally defines the nature of a computational system, sharpening our understanding of computation theory and its applications. In chapter two he generalizes his definition of a computational system, arguing that the concept of Turing computability itself is relative to the kind of support on which Turing machine operate. Chapter three completes the book's conceptual foundation, discussing a form of scientific explanation for real dynamical systems that Giunti calls "Galilean explanation." The book's fourth and final chapter develops the methodological thesis that all cognitive systems are dynamical systems. On Giunti's view, a dynamical approach is likely to benefit even those scientific explanations of cognition which are based on symbolic models. Giunti concludes by proposing a new modeling practice for cognitive science, one based on "Galilean models" of cognitive systems. Innovative, lucidly-written, and broad-ranging in its analysis, Computation, Dynamics, and Cognition will interest philosophers of science and mind, as well as cognitive scientists, computer scientists, and theorists of dynamical systems. This book elaborates a comprehensive picture of the application of dynamical methods to the study of cognition. Giunti argues that both computational systems and connectionist networks are special types of dynamical systems. He shows how this dynamical approach can be applied to problems of cognition, information processing, consciousness, meaning, and the relation between body and mind.

Computer science and physics have been closely linked since the birth of modern computing. In recent years, an interdisciplinary area has blossomed at the junction of these fields, connecting insights from statistical physics with basic computational challenges. Researchers have successfully applied techniques from the study of phase transitions to analyze NP-complete problems such as satisfiability and graph coloring. This is leading to a new understanding of the structure of these problems, and of how algorithms perform on them. Computational Complexity and Statistical Physics will serve as a standard reference and pedagogical aid to statistical physics methods in computer science, with a particular focus on phase transitions in combinatorial problems. Addressed to a broad range of readers, the book includes substantial background material along with current research by leading computer scientists, mathematicians, and physicists. It will prepare students and researchers from all of these fields to contribute to this exciting area.

Scientific descriptions of the climate have traditionally been based on the study of average meteorological values taken from different positions around the world. In recent years however it has become apparent that these averages should be considered with other statistics that ultimately characterize spatial and temporal variability. This book is designed to meet that need. It is based on a course in computational statistics taught by the author that arose from a variety of projects on the design and development of software for the study of climate change, using statistics and methods of random functions.

This book brings together the two disparate worlds of computational text analysis and biology and presents some of the latest methods and applications to proteomics, sequence analysis and gene expression data. Modern genomics generates large and comprehensive data sets but their interpretation requires an understanding of a vast number of genes, their complex functions, and interactions. Keeping up with the literature on a single gene is a challenge itself-for thousands of genes it is simply impossible. Here, Soumya Raychaudhuri presents the techniques and algorithms needed to access and utilize the vast scientific text, i.e. methods that automatically "read" the literature on all the genes. Including background chapters on the necessary biology, statistics and genomics, in addition to practical examples of interpreting many different types of modern experiments, this book is ideal for students and researchers in computational biology, bioinformatics, genomics, statistics and computer science.

With Computational Thinking in Sound, veteran educators Gena R. Greher and Jesse M. Heines provide the first book ever written for music fundamentals educators that is devoted specifically to music, sound, and technology. Using a student-centered approach that emphasizes project-based experiences, the book provides music educators with multiple strategies to explore, create, and solve problems with music and technology in equal parts. It also provides examples of hands-on activities that encourage students, alone and in groups, to explore the basic principles that underlie today's music technology and freely available multimedia creation tools. Computational Thinking in Sound is an effective tool for educators to introduce students to the complex process of computational thinking in the context of the creative arts through the more accessible medium of music.

This book presents a broad collection of models and computational methods - from atomistic to continuum - applied to crystal dislocations. Its purpose is to help students and researchers in computational materials sciences to acquire practical knowledge of relevant simulation methods. Because their behavior spans multiple length and time scales, crystal dislocations present a common ground for an in-depth discussion of a variety of computational approaches, including their relative strengths, weaknesses and inter-connections. The details of the covered methods are presented in the form of "numerical recipes" and illustrated by case studies. A suite of simulation codes and data files is made available on the book's website to help the reader "to learn-by-doing" through solving the exercise problems offered in the book.

1001 Computer Words You Need to Know explains and illuminates the essential vocabulary of computers and the Internet. This comprehensive, but never condescending guide to the language of the electronic age carefully defines and explains every term with a sample sentence, and many entries have supplementary notes. In addition, the book includes a number of quick miniguides to managing your online life - dealing with Windows and Macs (and sometimes *nix), burning CDs and downloading files, word processing, spread-sheeting, connecting to the Internet (dialup, cable, DSL, wireless) surfing, IMing and emailing, taking digital photos, coping with networks, memory, and drives, and just plain coping with your computer. The backmatter contains an extensive list of helpful websites and an essay about online language and etiquette.