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Probabilistic Reasoning In Multiagent Systems

Author: Yang Xiang
Publisher: Cambridge University Press
ISBN: 9781139434461
Size: 58.83 MB
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This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.

Advances In Probabilistic Graphical Models

Author: Peter Lucas
Publisher: Springer
ISBN: 3540689966
Size: 48.29 MB
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This book brings together important topics of current research in probabilistic graphical modeling, learning from data and probabilistic inference. Coverage includes such topics as the characterization of conditional independence, the learning of graphical models with latent variables, and extensions to the influence diagram formalism as well as important application fields, such as the control of vehicles, bioinformatics and medicine.

Advances In Practical Applications Of Agents And Multiagent Systems

Author: Yves Demazeau
Publisher: Springer Science & Business Media
ISBN: 9783642123849
Size: 32.35 MB
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PAAMS, the International Conference on Practical Applications of Agents and Multi-Agent Systems is an international yearly stage to present, to discuss, and to disseminate the latest advances and the most important outcomes related to real-world applications. It provides a unique opportunity to bring multi-disciplinary experts, academics and practitioners together to exchange their experience in the development of Agents and Multi-Agent Systems. This volume presents the papers that have been accepted for the 2010 edition. These articles capture the most innovative results and this year’s advances. Each paper has been reviewed by three different reviewers, from an international com-mittee composed of 82 members from 26 different countries. From the 66 submissions received, 19 were selected for full presentation at the conference, and 14 were accepted as short papers. Moreover, PAAMS'10 incorporated special ses-sions and workshops to complement the regular program, which included 85 ac-cepted papers.

Advances In Artificial Intelligence

Author: Osmar Zaiane
Publisher: Springer
ISBN: 3642384579
Size: 62.18 MB
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This book constitutes the refereed proceedings of the 25th Canadian Conference on Artificial Intelligence, Canadian AI 2012, held in Regina, SK, Canada, in May 2013. The 17 regular papers and 15 short papers presented were carefully reviewed and selected from 73 initial submissions and are accompanied by 8 papers from the Graduate Student Symposium that were selected from 14 submissions. The papers cover a variety of topics within AI, such as: information extraction, knowledge representation, search, text mining, social networks, temporal associations.

A Concise Introduction To Multiagent Systems And Distributed Artificial Intelligence

Author: Nikos Vlassis
Publisher: Morgan & Claypool Publishers
ISBN: 1598295276
Size: 37.13 MB
Format: PDF, ePub, Docs
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Multiagent systems is an expanding field that blends classical fields like game theory and decentralized control with modern fields like computer science and machine learning. This monograph provides a concise introduction to the subject, covering the theoretical foundations as well as more recent developments in a coherent and readable manner. The text is centered on the concept of an agent as decision maker. Chapter 1 is a short introduction to the field of multiagent systems. Chapter 2 covers the basic theory of singleagent decision making under uncertainty. Chapter 3 is a brief introduction to game theory, explaining classical concepts like Nash equilibrium. Chapter 4 deals with the fundamental problem of coordinating a team of collaborative agents. Chapter 5 studies the problem of multiagent reasoning and decision making under partial observability. Chapter 6 focuses on the design of protocols that are stable against manipulations by self-interested agents. Chapter 7 provides a short introduction to the rapidly expanding field of multiagent reinforcement learning. The material can be used for teaching a half-semester course on multiagent systems covering, roughly, one chapter per lecture.

Ieee Wic International Conference On Web Intelligence

Author: IEEE Computer Society. Technical Committee on Computational Intelligence
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
ISBN: 9780769519326
Size: 60.50 MB
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Web intelligence (WI) is a field of scientific research and development that deals with the fundamental roles and practical impacts of artificial intelligence (AI) and advanced information technology (IT) on the next generation of Web-empowered products, systems, services, and activities. Following the great success of WI 2001, WI 2003 covers the latest the state-of-the-art research in WI technologies and looks to cross-fertilize ideas on the development of Web-based intelligent information systems among the different domains.