Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations

Yoav Shoham, Kevin Leyton-Brown

"The integration of methodologies that study different aspects of interactive strategic systems is of vital importance in modern society. Through excellent side-by-side presentation of the main approaches in computer science, game theory and economics, this pioneering textbook is a major advance towards the education of a better-equipped generation of computer scientists as well as social scientists." 
Ehud Kalai, Northwestern University

"This is a rich and comprehensive text on multiagent systems, written by two of the leading researchers in the area in an engaging and accessible style. It is unique in covering the diverse foundations of multiagent systems, including logic. Its extensive treatment of the interplay between computer science and game theory will define how the subject should be taught. I recommend the book for graduate students and advanced undergraduates, as well as researchers in both computer science and economics trying to learn the basics of the field." 
Joseph Halpern, Cornell University

"With the emergence of the Internet, the focus of much of the research in computer science and in artificial intelligence is shifting from the the study of the single program to the study of the interactions among different computers and programs. Multiagent Systems presents for the first time this cutting-edge research in a textbook form. The book transcends the traditional boundaries of artificial intelligence and touches all aspects of multiagent systems: from artificial intelligence to algorithms to game theory, to logic, and beyond. Written by leaders in this research area, this book is certain to become the textbook of choice for classes on multiagent systems." 
Noam Nisan, Hebrew University

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Multicriterion Decision in Management: Principles and Practice

International Series in Operations Research & Management Science

Jean-Charles Pomerol, Sergio Barba-Romero

Multicriterion Decision in Management: Principles and Practice is the first multicriterion analysis book devoted exclusively to discrete multicriterion decision making. Typically, multicriterion analysis is used in two distinct frameworks: Firstly, there is multiple criteria linear programming, which is an extension of the results of linear programming and its associated algorithms. Secondly, there is discrete multicriterion decision making, which is concerned with choices among a finite number of possible alternatives such as projects, investments, decisions, etc. This is the focus of this book. The book concentrates on the basic principles in the domain of discrete multicriterion analysis, and examines each of these principles in terms of their properties and their implications. In multicriterion decision analysis, any optimum in the strict sense of the term does not exist. Rather, multicriterion decision making utilizes tools, methods, and thinking to examine several solutions, each having their advantages and disadvantages, depending on one's point of view. Actually, various methods exist for reaching a good choice in a multicriterion setting and even a complete ranking of the alternatives. The book describes and compares these methods, so-called `aggregation methods', with their advantages and their shortcomings. Clearly, organizations are becoming more complex, and it is becoming harder and harder to disregard complexity of points of view, motivations, and objectives. The day of the single objective (profit, social environment, etc. ) is over and the wishes of all those involved in all their diversity must be taken into account. To do this, a basic knowledge of multicriterion decision analysis is necessary. The objective of this book is to supply that knowledge and enable it to be applied. The book is intended for use by practitioners (managers, consultants), researchers, and students in engineering and business.

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Final Jeopardy: Man vs. Machine and the Quest to Know Everything Stephen Baker

What if there were a computer that could answer virtually any question? IBM engineers are developing such a machine, teaching it to compete on the quiz show Jeopardy. In February 2011, it will face off in a nationally televised game against two of the game’s greatest all-time winners, Ken Jennings and Brad Rutter. Final Jeopardy tells the riveting story behind the match.

Final Jeopardy carries readers on a captivating journey from the IBM lab to the podium. The story features brilliant Ph.D.s, Hollywood moguls, knowledge-obsessed Jeopardy masters — and a very special collection of silicon and circuitry named Watson. It is a classic match of Man vs. Machine, not seen since Deep Blue bested chess grandmaster Garry Kasparov. But Watson will need to do more than churn through chess moves or find a relevant web page. It will have to understand language, including puns and irony, and master everything from history and literature to science, arts, and entertainment.

At its heart, Final Jeopardy is about the future of knowledge. What can we teach machines? What will Watson’s heirs be capable of in ten or twenty years? And where does that leave humans? As fast and fun as the game itself, Final Jeopardy shows how smart machines will fit into our world — and how they’ll disrupt it.

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Encyclopedia of Machine Learning Claude Sammut, Geoffrey I. Webb

About the Author

Claude Sammut is a Professor of Computer Science and Engineering at the University of New South Wales, Australia, and Head of the Artificial Intelligence Research Group. He is the UNSW node Director of the ARC Centre of Excellence for Autonomous Systems and a member of the joint ARC/NH&MRC project on Thinking Systems. He is on the editorial boards of the Journal of Machine Learning Research, the Machine Learning Journal and New Generation Computing, and was the chairman of the 2007 International Conference on Machine Learning.

Geoffrey I. Webb is research professor in the faculty of Information Technology at Monash University, Melbourne, Australia. He has published more than 150 scientific papers and is the author of the data mining software package Magnum Opus. His research areas include strategies for strengthening the Naïve Bayes machine learning technique, K-optimal pattern discovery, and work on Occam’s razor. He is editor-in-chief of Springer’s Data Mining and Knowledge Discovery journal, as well as being on the editorial board of Machine Learning.

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Advances in Visual Computing: Second International Symposium

ISVC 2006, Lake Tahoe, NV, USA, November 6-8, 2006, Proceedings, Part II (Lecture Notes ... Vision, Pattern Recognition, and Graphics)
Richard Boyle, Bahram Parvin, Darko Koracin, Ara Nefian, Gopi Meenakshisundaram, Valerio Pascucci, Jiri Zara, Jose Molineros, Holger Theisel, Tom Malzbender

   The two volume set LNCS 4291 and LNCS 4292 constitutes the refereed proceedings of the Second International Symposium on Visual Computing, ISVC 2006, held in Lake Tahoe, NV, USA in November 2006.

The 65 revised full papers and 56 poster papers presented together with 57 papers of ten special tracks were carefully reviewed and selected from more than 280 submissions. The papers cover the four main areas of visual computing.

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Computational Methods in Environmental Fluid Mechanics Olaf Kolditz

"The book is warmly commended. Graduates/advanced undergraduate students, engineers, and researchers in environmental fluid dynamics, will profit from the book. The bibliography provides an important guide for further reading. It is hard to think of anyone who is concerned with the role of fluids in environment, who will not gain by reading this book and having it available for reference." (Current Engineering Practice, Vol. 45 (3-4), 2002-2003)

From the Back Cover Fluids play an important role in environmental systems appearing as surface water in rivers, lakes, and coastal regions or in the subsurface as well as in the atmosphere. Mechanics of environmental fluids is concerned with fluid motion, associated mass and heat transport as well as deformation processes in subsurface systems. In this textbook the fundamental modelling approaches based on continuum mechanics for fluids in the environment are described, including porous media and turbulence. Numerical methods for solving the process governing equations as well as its object-oriented computer implementation are discussed and illustrated with examples. Finally the application of computer models in civil and environmental engineering is demonstrated.

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An Introduction to MultiAgent Systems Michael Wooldridge

From the Back Cover "A thoroughly revised and updated book, written by one of the leading researchers in the field. This excellent book provides a wonderful introduction and a comprehensive exposition of the increasingly important field of multi-agent systems."
—Professor Nick Jennings FREng
Intelligence, Agents, Multimedia Group, Electronics and Computer Science, University of Southampton

Multiagent systems are a new paradigm for understanding and building distributed systems, where it is assumed that the computational components are autonomous: able to control their own behaviour in the furtherance of their own goals. The first edition of An Introduction to Multiagent Systems was the first contemporary textbook in the area, and became the standard undergraduate reference work for the field. This second edition has been extended with substantial new material on recent developments in the field, and has been revised and updated throughout. It provides a comprehensive, coherent, and readable introduction to the theory and practice of multiagent systems, while presenting a wealth of discussion topics and pointers into more advanced issues for those wanting to dig deeper.

Key new features include:

• dedicated new chapters on ontologies, voting, auctions, bargaining, coalition formation, and argumentation, reflecting recent research directions and new results;
• "mind maps" to illustrate key concepts and ideas - an essential study and revision aid;
• 590 literature references, revised, updated, and extended to reflect the state of the art in agent research and development.

Designed and written specifically for computing undergraduates, the book comes with a rich repository of online teaching materials, including a complete set of lecture slides.

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Uncertainty Analysis in Engineering and Sciences

Fuzzy Logic, Statistics, and Neural Network Approach (International Series in Intelligent Technologies)
Madan M. Gupta, Bilal M. Ayyub

Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach examines the use of newly developed analytical tools for studying uncertainty analysis in engineering, control systems, and the sciences. It is the work of 38 experts who have written chapters on newly developed analytical methods - fuzzy logic, neural networks, simulation, and Bayesian techniques - and have applied them to uncertainty phenomena arising out of information and knowledge problems in the fields of engineering and the sciences. The book is divided into the following parts: Part I reports the theoretical studies on uncertainty types, models and measures; Part II reviews the applications of uncertain theoretical tools to engineering systems; Part III describes the methodologies of fuzzy-neural data analysis and forecasting; Part IV presents two chapters on fuzzy-neuro systems; and Part V describes the methodologies for fuzzy decision making and optimization and their computational methods. The Editors provide a concluding chapter on uncertainty and uncertainty modeling. This is a carefully developed book that treats the topic of uncertainty from fresh perspectives and in depth.

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Robots and Biological Systems: Towards a New Bionics?

Proceedings of the NATO Advanced Workshop on Robots and Biological Systems, held at II Ciocco, 26-30, 1989 (Nato ASI Subseries F)

Paolo Dario, Giulio Sandini, Patrick Aebischer

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