Students explore the idea that thinking is a form of computation by learning to write simple computer programs for tasks that require thought.This book guides students through an exploration of the idea that thinking might be understood as a form of computation. Students make the connection between thinking and computing by learning to write computer programs for a variety of tasks that require thought, including solving puzzles, understanding natural language, rec...

What can artificial intelligence tell us about the mind and intelligent behavior? A computer science expert explores the importance of common sense in everyday decision making.What can artificial intelligence teach us about the mind? If AI’s underlying concept is that thinking is a computational process, then how can computation illuminate thinking? It’s a timely question. Artificial intelligence is all the rage, and the buzziest AI buzz surrounds adap...

Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed. This landmark text takes the central...

How we can create artificial intelligence with broad, robust common sense rather than narrow, specialized expertise.It’s sometime in the not-so-distant future, and you send your fully autonomous self-driving car to the store to pick up your grocery order. The car is endowed with as much capability as an artificial intelligence agent can have, programmed to drive better than you do. But when the car encounters a traffic light stuck on red, it just sits there—indefin...

Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don’t need any programming or linguistics experience to get started.Using detailed examples at every step, you’ll learn how the MATTER Annotation Developm...

Understanding Minimalism, first published in 2005, is an introduction to the Minimalist Program - the model of syntactic theory within generative linguistics. Accessibly written, it presents the basic principles and techniques of the minimalist program, looking firstly at analyses within Government and Binding Theory (the Minimalist Program's predecessor), and gradually introducing minimalist alternatives. Minimalist models of grammar are presented in a step-by-step fashion, and the ways i...

Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts.A separate chapter is dedicated to each of the three introduced topics, followi...

Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level.Euzenat and Shva...

The essays in this important collection explore wide-ranging aspects of the syntax and semantics of human languages. Key topics covered include movement phenomena and the syntax of logical form, methods in generative linguistics and the role of rules vs. principles in syntactic theory. This volume makes a vital contribution to substantive and methodological debates in linguistic theory.

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...

This comprehensive reference work provides an overview of the concepts, methodologies, and applications in computational linguistics and natural language processing (NLP).Features contributions by the top researchers in the field, reflecting the work that is driving the discipline forwardIncludes an introduction to the major theoretical issues in these fields, as well as the central engineering applications that the work has producedPresents the major deve...