Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications

By: Vijayan Sugumaran (Editor)

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Hardcover | 1 December 2008

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452 Pages

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27.94 x 21.59 x 2.54

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Cutting-edge developments in artificial intelligence are now driving applications that are only hinting at the level of value they will soon contribute to organizations, consumers, and societies across all domains.""Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications"" offers an enriched set of research articles in artificial intelligence (AI), covering significant AI subjects such as information retrieval, conceptual modeling, supply chain demand forecasting, and machine learning algorithms. This comprehensive collection provides libraries with a one-stop resource to equip the academic, industrial, and managerial communities with an in-depth look into the most pertinent AI advances that will lead to the most valuable applications.

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Engineering & Technology Technology in General Databases Electronics & Communications Engineering Communications Engineering & Telecommunications

Designing multi-agent systems from logic specifications : a case study	p. 1
Multi-agent architecture for knowledge-driven decision support	p. 28
A decision support system for trust formalization	p. 47
Using misunderstanding and discussion in dialog as a knowledge acquisition or enhancement process	p. 65
Improving e-trade auction volume by consortium	p. 91
Extending loosely coupled federated information systems using agent technology	p. 116
Modeling fault tolerant and secure mobile agent execution in distributed systems	p. 132
Search engine performance comparisons	p. 148
A user-centered approach for information retrieval	p. 165
Classification and retrieval of images from databases using rough set theory	p. 179
Supporting text retrieval by typographical term weighing	p. 199
Web mining by automatically organizing Web pages into categories	p. 214
Mining matrix pattern from mobile users	p. 232
Conceptual modeling of events for active information systems	p. 261
Information modeling and the problem of universals	p. 273
Empirical inference of numerical information into causal strategy models by means of artificial intelligence	p. 290
Improving mobile Web navigation using N-grams prediction models	p. 314
Forecasting supply chain demand using machine learning algorithms	p. 328
Supporting demand supply network optimization with Petri nets	p. 366
Compilation of references	p. 384
About the contributors	p. 416
Index	p. 423
Table of Contents provided by Blackwell. All Rights Reserved.

Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications

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Hardcover

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