Bücher veröffentlicht von MIT Press

The first volume contains several classic papers, including the many contributions to the theory of distortions in the 1960s, which laid the foundations of the postwar theory of commercial policy.

Advanced statistical modeling and knowledge representation techniques for a newly emerging area of machine learning and probabilistic reasoning; includes introductory material, tutorials for different proposed approaches, and applications.Handling inherent uncertainty and exploiting compositional structure are fundamental to understanding and designing large-scale systems. Statistical relational learning builds on ideas from probability theory and statistics to address uncertainty while incorporating tools from logic, databases and programming languages to represent structure. In Introduction to Statistical Relational Learning, leading researchers in this emerging area of machine learning describe current formalisms, models, and algorithms that enable effective and robust reasoning about richly structured systems and data. The early chapters provide tutorials for material used in later chapters, offering introductions to representation, inference and learning in graphical models, and logic. The book then describes object-oriented approaches, including probabilistic relational models, relational Markov networks, and probabilistic entity-relationship models as well as logic-based formalisms including Bayesian logic programs, Markov logic, and stochastic logic programs. Later chapters discuss such topics as probabilistic models with unknown objects, relational dependency networks, reinforcement learning in relational domains, and information extraction. By presenting a variety of approaches, the book highlights commonalities and clarifies important differences among proposed approaches and, along the way, identifies important representational and algorithmic issues. Numerous applications are provided throughout.

This new anthology will serve as an ideal introduction to phenomenology for analytic philosophers, both as a text and as the single most useful source book on Husserl for cognitive scientists.

The task of archiving was once entrusted only to museums, libraries, and other institutions that acted as repositories of culture in material form. But with the rise of digital networked media, a multitude of self-designated archivists -- fans, pirates, hackers -- have become practitioners of cultural preservation on the Internet. These nonprofessional archivists have democratized cultural memory, building freely accessible online archives of whatever content they consider suitable for digital preservation. In Rogue Archives, Abigail De Kosnik examines the practice of archiving in the transition from print to digital media, looking in particular at Internet fan fiction archives.De Kosnik explains that media users today regard all of mass culture as an archive, from which they can redeploy content for their own creations. Hence, "remix culture" and fan fiction are core genres of digital cultural production. De Kosnik explores, among other things, the anticanonical archiving styles of Internet preservationists; the volunteer labor of online archiving; how fan archives serve women and queer users as cultural resources; archivists' efforts to attract racially and sexually diverse content; and how digital archives adhere to the logics of performance more than the logics of print. She also considers the similarities and differences among free culture, free software, and fan communities, and uses digital humanities tools to quantify and visualize the size, user base, and rate of growth of several online fan archives.

Solutions manual for an innovative textbook accessible not only to graduate students in mathematical finance and financial engineering but also to undergraduate students and graduate students not specializing in finance.

The second volume presents essays that have opened up new areas of analysis in the theory of international trade and in the associated fields of public finance and developmental economics.

This comprehensive collection of twenty-nine readings covers artificial intelligence from its historical roots to current research directions and practice. With its helpful critique of the selections, extensive bibliography, and clear presentation of the material, Computation and Intelligence will be a useful adjunct to any course in AI as well as a handy reference for professionals in the field. The book is divided into five parts. The first part contains papers that present or discuss foundational ideas linking computation and intelligence, typified by A. M. Turing's "Computing Machinery and Intelligence". The second part, Knowledge Representation, presents a sampling of the numerous representational schemes - by Newell, Minsky, Collins and Quillian, Winograd, Schank, Hayes, Holland, McClelland, Rumelhart, Hinton, and Brooks. The third part, Weak Method Problem Solving, focuses on the research and design of syntax based problem solvers, including the most famous of these, the Logic Theorist and GPS. The fourth part, Reasoning in Complex and Dynamic Environments, presents a broad spectrum of the AI communities' research in knowledge-intensive problem solving, from McCarthy's early design of systems with "common sense" to model based reasoning. The two concluding selections, by Marvin Minsky and by Herbert Simon, respectively, present the recent thoughts of two of AI's pioneers who revisit the concepts and controversies that have developed during the evolution of the tools and techniques that make up the current practice of artificial intelligence.

This fascinating investigation on the borderlines of metaphysics, everyday geometry, and the theory of perception seeks to answer two basic questions: Do holes really exist? And if so, what are they? Holes are among entities that down-to-earth philosophers would like to expel from their ontological inventory. Casati and Varzi argue in favor of their existence and explore the consequences of this unorthodox approach—odd as these might appear. They examine the ontology of holes, their geometry, their part-whole relations, their identity, their causal role, and the ways we perceive them.A Bradford Book