Books published by MIT Press Ltd

Scientists attempt to decode what may be a message from intelligent beings in outer space.By pure chance, scientists detect a signal from space that may be communication from rational beings. How can people of Earth understand this message, knowing nothing about the senders—even whether or not they exist? Written as the memoir of a mathematician who participates in the government project (code name: His Master's Voice) attempting to decode what seems to be a message from outer space, this classic novel shows scientists grappling with fundamental questions about the nature of reality, the confines of knowledge, the limitations of the human mind, and the ethics of military-sponsored scientific research.

The definitive book on leadership in the digital era: why digital technologies call for leadership that emphasizes creativity, collaboration, and inclusivity.

Are we alone in the universe? If not, where is everybody? An engaging exploration of one of the most important unsolved problems in science.Everything we know about how planets form and how life arises suggests that human civilization on Earth should not be unique. We ought to see abundant evidence of extraterrestrial activity—but we don't. Where is everybody? In this volume in the MIT Press Essential Knowledge series, science and technology writer Wade Roush examines one of the great unsolved problems in science: is there life, intelligent or otherwise, on other planets? This paradox (they're bound to be out there; but where are they?), first formulated by the famed physicist Enrico Fermi, has fueled decades of debate, speculation, and, lately, some actual science. Roush lays out the problem in its historical and modern-day context and summarizes the latest thinking among astronomers and astrobiologists. He describes the long history of speculation about aliens (we've been debating the idea for thousands of years); the emergence of SETI (the Search for Extraterrestrial Intelligence) as a scientific discipline in the 1960s, and scientists' use of radio and optical techniques to scan for signals; and developments in astrobiology (the study of how life might arise in non-Earth like environments) and exoplanet research (the discovery of planets outside our solar system). Finally, he discusses possible solutions to the Fermi Paradox and suggests way to refocus SETI work that might increase the chances of resolving the paradox—and finding extraterrestrials.

How game designers can use the psychological phenomenon of loss aversion to shape player experience.Getting something makes you feel good, and losing something makes you feel bad. But losing something makes you feel worse than getting the same thing makes you feel good. So finding $10 is a thrill; losing $10 is a tragedy. On an "intensity of feeling” scale, loss is more intense than gain. This is the core psychological concept of loss aversion, and in this book game creator Geoffrey Engelstein explains, with examples from both tabletop and video games, how it can be a tool in game design. Loss aversion is a profound aspect of human psychology, and directly relevant to game design; it is a tool the game designer can use to elicit particular emotions in players. Engelstein connects the psychology of loss aversion to a range of phenomena related to games, exploring, for example, the endowment effect—why, when an object is ours, it gains value over an equivalent object that is not ours—as seen in the Weighted Companion Cube in the game Portal; the framing of gains and losses to manipulate player emotions; Deal or No Deal's use of the utility theory; and regret and competence as motivations, seen in the context of legacy games. Finally, Engelstein examines the approach to Loss Aversion in three games by Uwe Rosenberg, charting the designer's increasing mastery.

An examination of the many complex aspects of game audio, from the perspectives of both sound design and music composition.

An argument that health is optimal responsiveness and is often best treated at the system level.Medical education centers on the venerable "no-fault” concept of homeostasis, whereby local mechanisms impose constancy by correcting errors, and the brain serves mainly for emergencies. Yet, it turns out that most parameters are not constant; moreover, despite the importance of local mechanisms, the brain is definitely in charge. In this book, the eminent neuroscientist Peter Sterling describes a broader concept: allostasis (coined by Sterling and Joseph Eyer in the 1980s), whereby the brain anticipates needs and efficiently mobilizes supplies to prevent errors.Allostasis evolved early, Sterling explains, to optimize energy efficiency, relying heavily on brain circuits that deliver a brief reward for each positive surprise. Modern life so reduces the opportunities for surprise that we are driven to seek it in consumption: bigger burgers, more opioids, and innumerable activities that involve higher carbon emissions. The consequences include addiction, obesity, type 2 diabetes, and climate change. Sterling concludes that solutions must go beyond the merely technical to restore possibilities for daily small rewards and revivify the capacities for egalitarianism that were hard-wired into our nature.Sterling explains that allostasis offers what is not found in any medical textbook: principled definitions of health and disease: health as the capacity for adaptive variation and disease as shrinkage of that capacity. Sterling argues that since health is optimal responsiveness, many significant conditions are best treated at the system level.

An introduction to computational thinking that traces a genealogy beginning centuries before the digital computer.A few decades into the digital era, scientists discovered that thinking in terms of computation made possible an entirely new way of organizing scientific investigation; eventually, every field had a computational branch: computational physics, computational biology, computational sociology. More recently, "computational thinking” has become part of the K-12 curriculum. But what is computational thinking? This volume in the MIT Press Essential Knowledge series offers an accessible overview, tracing a genealogy that begins centuries before digital computers and portraying computational thinking as pioneers of computing have described it. The authors explain that computational thinking (CT) is not a set of concepts for programming; it is a way of thinking that is honed through practice: the mental skills for designing computations to do jobs for us, and for explaining and interpreting the world as a complex of information processes. Mathematically trained experts (known as "computers”) who performed complex calculations as teams engaged in CT long before electronic computers. The authors identify six dimensions of today's highly developed CT—methods, machines, computing education, software engineering, computational science, and design—and cover each in a chapter. Along the way, they debunk inflated claims for CT and computation while making clear the power of CT in all its complexity and multiplicity.

Investigating the concepts and material realities of energy coursing through the arts: a foundational text.This book investigates energies—in the plural, the energies embedded and embodied in everything under the sun— as they are expressed in the arts. With contributions from scholars and critics from the visual arts, art history, anthropology, music, literature, and the history of science, it offers the first multidisciplinary investigation of the concepts and material realities of energy coursing through the arts. Just as Douglas Kahn's earlier books helped introduce sound as a category for study in the arts, this new volume will be a foundational volume for future explorers in a largely uncharted domain. The modern concept of energy is only two hundred years old—an abstraction grounded in extraction—but this book takes a more expansive view. It opens with a clap: the sonic energies in a ceremony of the indigenous Goolarabooloo people of Australia. Other chapters explore the energies of photography; responses of artists in the early twentieth century—including Marcel Duchamp—to scientific discoveries in electricity and electromagnetism; the aestheticization of entropy in works by Hans Haacke and Robert Smithson; free-jazz musician Milford Graves's cross-cultural engagement with music, science, and spiritualism; energy field performance; and the self-generating energy of rumor and gossip as artwork. Contributors include such leading scholars as Linda Dalrymple Henderson, John Tresch, and Caroline A. Jones. Practicing artists and students of art history will find Energies in the Arts an essential work.ContributorsSusan Ballard, Jennifer Biddle, Marcus Boon, Joan Brassil, Steven Connor, Milford Graves, Daniel Hackbarth, Linda Dalrymple Henderson, Caroline A. Jones, Douglas Kahn, David Mather, Stephen Muecke, James Nisbet, Daniela Silvestrin, Michael Taussig, John Tresch, Melissa Warak

Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.

A new edition of a book, written in a humorous question-and-answer style, that shows how to implement and use an elegant little programming language for logic programming.

A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges.The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges.It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. It is closely related to the fields of data mining and machine learning, but broader in scope. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. Finally, it considers the future impact of data science and offers principles for success in data science projects.