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Multiagent Systems, Second Edition

Edited by Gerhard Weiss

Multiagent systems are made up of multiple interacting intelligent agents—computational entities to some degree autonomous and able to cooperate, compete, communicate, act flexibly, and exercise control over their behavior within the frame of their objectives. They are the enabling technology for a wide range of advanced applications relying on distributed and parallel processing of data, information, and knowledge relevant in domains ranging from industrial manufacturing to e-commerce to health care.

Interactive Visualization

Insight through Inquiry
By Bill Ferster

Interactive visualization is emerging as a vibrant new form of communication, providing compelling presentations that allow viewers to interact directly with information in order to construct their own understandings of it. Building on a long tradition of print-based information visualization, interactive visualization utilizes the technological capabilities of computers, the Internet, and computer graphics to marshal multifaceted information in the service of making a point visually.

Machine Learning

A Probabilistic Perspective
By Kevin P. Murphy

Today’s Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

Building Mobile Experiences

By Frank Bentley and Edward Barrett

The mobile device is changing the ways we interact with each other and with the world. The mobile experience is distinct from the desktop or laptop experience; mobile apps require a significantly different design philosophy as well as design methods that reflect the unique experience of computing in the world. This book presents an approach to designing mobile media that takes advantage of the Internet-connected, context-aware, and media-sharing capabilities of mobile devices.

A Semantic Web Primer, Third Edition

By Grigoris Antoniou, Paul Groth, Frank van Harmelen and Rinke Hoekstra

The development of the Semantic Web, with machine-readable content, has the potential to revolutionize the World Wide Web and its uses. A Semantic Web Primer provides an introduction and guide to this continuously evolving field, describing its key ideas, languages, and technologies.

Characteristics of Games

By George Skaff Elias, Richard Garfield and K. Robert Gutschera

Characteristics of Games offers a new way to understand games: by focusing on certain traits--including number of players, rules, degrees of luck and skill needed, and reward/effort ratio--and using these characteristics as basic points of comparison and analysis. These issues are often discussed by game players and designers but seldom written about in any formal way. This book fills that gap. By emphasizing these player-centric basic concepts, the book provides a framework for game analysis from the viewpoint of a game designer.

Foundations of Machine Learning

By Mehryar Mohri, Afshin Rostamizadeh and Ameet Talwalkar

This graduate-level textbook introduces fundamental concepts and methods in machine learning. It describes several important modern algorithms, provides the theoretical underpinnings of these algorithms, and illustrates key aspects for their application. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics.

Foundations of 3D Computer Graphics

By Steven J. Gortler

Computer graphics technology is an amazing success story. Today, all of our PCs are capable of producing high-quality computer-generated images, mostly in the form of video games and virtual-life environments; every summer blockbuster movie includes jaw-dropping computer generated special effects. This book explains the fundamental concepts of 3D computer graphics.

Boosting

Foundations and Algorithms
By Robert E. Schapire and Yoav Freund

Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate “rules of thumb.” A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.

Thinking as Computation

A First Course
By Hector J. Levesque

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, recognizing objects in visual scenes, planning courses of action, and playing strategic games.

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