Distributed Artificial Intelligence, Agent Technology, and Collaborative Applications (Advances in Intelligent Information Technologies)

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. Title......Page 2 Table of Contents......Page 6 Detailed Table of Contents......Page 10 Preface......Page 18 Designing Multi-Agent Systems from Logic Specifications: A Case Study......Page 26 Multi-Agent Architecture for Knowledge-Driven Decision Support......Page 53 A Decision Support System for Trust Formalization......Page 72 Using Misunderstanding and Discussion in Dialog as a Knowledge Acquisition or Enhancement Process......Page 90 Improving E-Trade Auction Volume by Consortium......Page 116 Extending Loosely Coupled Federated Information Systems Using Agent Technology......Page 141 Modeling Fault Tolerant and Secure Mobile Agent Execution in Distributed Systems......Page 157 Search Engine Performance Comparisons......Page 173 A User-Centered Approach for Information Retrieval......Page 190 Classification and Retrieval of Images from Databases Using Rough Set Theory......Page 204 Supporting Text Retrieval by Typographical Term Weighting......Page 224 Web Mining by Automatically Organizing Web Pages into Categories......Page 239 Mining Matrix Pattern from Mobile Users......Page 257 Conceptual Modeling of Events for Active Information Systems......Page 286 Information Modeling and the Problem of Universals......Page 298 Empirical Inference of Numerical Information into Causal Strategy Models by Means of Artificial Intelligence......Page 315 Improving Mobile Web Navigation Using N-Grams Prediction Models......Page 339 Forecasting Supply Chain Demand Using Machine Learning Algorithms......Page 353 Supporting Demand Supply Network Optimization with Petri Nets......Page 391 Compilation of References......Page 409 About the Contributors......Page 441 Index......Page 448 'This book is a catalyst for emerging research in intelligent information, specifically artificial intelligent technologies and applications to assist in improving productivity in many roles such as assistants to human operators and autonomous decision-making components of complex systems'--Provided by publisher.