The challenges we face in education, health care, and social welfare are multifaceted, reflecting the complex systems in which we live. Out of urgency and often the best of intentions, organizations implement new policies, technologies, and other innovations to tackle these issues, and hope for the best. However, addressing these challenges requires more than heroic individuals with silver-bullet solutions. We need teams with diverse expertise that know how to learn together and use their ...

What will the end of the world be like?Plague or nuclear fire? Asteroids or floods?Divine wrath or people meddling with what should have been left alone?The apocalypse may come in the future, but what apocalypses might have occurred if history had played out differently? What if nukes had flown during the Cuban Missile Crisis? What if an asteroid had been on a collision course with Earth before the first person could set foot on the Moon? What if humanity destroyed it...

This special issue collects enhanced and extended versions of papers that were presented at the Symposium on Spatial Vagueness, Uncertainty, and Granularity held in October 2001. The contributions examine fundamental problems in the analysis of spatial vagueness and uncertainty, and the editors hope this selection stimulates further investigation in this growing subfield of the theory of spatial information.

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics ...

This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficult...

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provid...

Human language seems to have arisen roughly within the last 50-100,000 years. In evolutionary terms, this is the mere blink of an eye. If this is correct, then much of what we consider distinctive to language must in fact involve operations available in pre-linguistic cognitive domains. In this book Norbert Hornstein, one of the most influential linguists working on syntax, discusses a topical set of issues in syntactic theory, including a number of original proposals at the cutting edge o...

Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this b...

To enhance marketing analytics, approximate and inductive reasoning can be applied to handle uncertainty in individual marketing models. This book demonstrates the use of fuzzy logic for classification and segmentation in marketing campaigns. Based on practical experience as a data analyst and on theoretical studies as a researcher, the author explains fuzzy classification, inductive logic and the concept of likelihood and introduces a blend of Bayesian and Fuzzy Set approaches, allowing r...

This volume describes and analyzes in a systematic way the great contributions of the philosopher Krister Segerberg to the study of real and doxastic actions. Following an introduction which functions as a roadmap to Segerberg's works on actions, the first part of the book covers relations between actions, intentions and routines, dynamic logic as a theory of action, agency, and deontic logics built upon the logics of actions. The second section explores belief revision and update, iterate...

Multilingual Natural Language Processing Applications is the first comprehensive single-source guide to building robust and accurate multilingual NLP systems. Edited by two leading experts, it integrates cutting-edge advances with practical solutions drawn from extensive field experience.Part I introduces the core concepts and theoretical foundations of modern multilingual natural language processing, presenting today’s best practices for understanding wor...

This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances in statistical learning theory. SVMs deliver state-of-the-art performance in real-world applications such as text categorisation, hand-written character recognition, image classification, biosequences analysis, etc., and are now established as one of the standard tools for machine learning and data mining. Students will find the book both stimulating and acc...