All design is situated—carried out from an embedded position. Design involves many participants and encompasses a range of interactions and interdependencies among designers, designs, design methods, and users. Design is also multidisciplinary, extending beyond the traditional design professions into such domains as health, culture, education, and transportation.
Complex communicating computer systems—computers connected by data networks and in constant communication with their environments—do not always behave as expected. This book introduces behavioral modeling, a rigorous approach to behavioral specification and verification of concurrent and distributed systems. It is among the very few techniques capable of modeling systems interaction at a level of abstraction sufficient for the interaction to be understood and analyzed.
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts.
ALIFE 14, the Fourteenth International Conference on the Synthesis and Simulation of Living Systems, presents the current state of the art of Artificial Life—the highly interdisciplinary research area on artificially constructed living systems, including mathematical, computational, robotic, and biochemical ones. The understanding and application of such generalized forms of life, or “life as it could be,” have been producing significant contributions to various fields of science and engineering.
Computers were first conceived as “thinking machines,” but in the twenty-first century they have become social machines, online places where people meet friends, play games, and collaborate on projects. In this book, Judith Donath argues persuasively that for social media to become truly sociable media, we must design interfaces that reflect how we understand and respond to the social world.
Our contemporary concerns about food range from food security to agricultural sustainability to getting dinner on the table for family and friends. This book investigates food issues as they intersect with participatory Internet culture—blogs, wikis, online photo- and video-sharing platforms, and social networks—in efforts to bring about a healthy, socially inclusive, and sustainable food future.
Music in video games is often a sophisticated, complex composition that serves to engage the player, set the pace of play, and aid interactivity. Composers of video game music must master an array of specialized skills not taught in the conservatory, including the creation of linear loops, music chunks for horizontal resequencing, and compositional fragments for use within a generative framework.
This book offers the definitive guide to the theory and practice of disaster robotics. It can serve as an introduction for researchers and technologists, a reference for emergency managers, and a textbook in field robotics. Written by a pioneering researcher in the field who has herself participated in fifteen deployments of robots in disaster response and recovery, the book covers theory and practice, the history of the field, and specific missions.
Today designers often focus on making technology easy to use, sexy, and consumable. In Speculative Everything, Anthony Dunne and Fiona Raby propose a kind of design that is used as a tool to create not only things but ideas. For them, design is a means of speculating about how things could be—to imagine possible futures. This is not the usual sort of predicting or forecasting, spotting trends and extrapolating; these kinds of predictions have been proven wrong, again and again.
This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models. It avoids mathematical argumentation, often a stumbling block for students, teaching algorithmic thought rather than proofs and logic. This approach allows the student to learn a large number of algorithms within a relatively short span of time. Algorithms are explained through brief, informal descriptions, illuminating examples, and practical exercises.