Constructing Intelligent Agents Using Java: Professional Developer's Guide (Professional Developer's Guide Series) - Softcover

Bigus, Joseph P; Bigus, Jennifer

Softcover

ISBN 10: 047139601X ISBN 13: 9780471396017

Verlag: John Wiley & Sons, 2001

Inhaltsangabe

Ein hochmoderner Leitfaden zur Erstellung intelligenter Web-basierter Anwendungen mit Java Joseph und Jennifer Bigus Update und Erweiterung ihres Buches zum Erstellen intelligenter Web-basierter Anwendungen mit Java. Dieses praktische Buch ist für Netzwerkprogrammierer oder Webentwickler ausgerichtet, die zuvor Agenten in Smalltalk oder C++ programmiert haben, erklärt im Detail, wie man Agenten, die lernen und wettbewerbsfähig sind, einschließlich Designprinzipien und tatsächlicher Code für persönliche Agenten, Netzwerk- oder Webagenten, Multiagent-Systeme und kommerzielle Agenten konstruiert. Die neue und überarbeitete Abdeckung umfasst Agent-Tools, Agent-Anwendungen für Web-Anwendungen (einschließlich Personalisierung, Cross-Selling, und E-Commerce) und zusätzliche KI-Technologien wie Fuzzy-Logik und genetische Algorithmen.

Über diesen Titel

Über die Autorin bzw. den Autor

JOSEPH P. BIGUS, PhD, is a senior technical staff member and research project leader at the IBM T. J. Watson Research Center. Dr. Bigus has led the development of neural network, data mining, and agent technologies at IBM.
JENNIFER BIGUS is the principal consultant at Bigus Technologies Inc., where she designs and develops Java and e-business applications. Jennifer played a key role in bringing Java and enterprise Java applications to the IBM AS/400 server.

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An essential guide to intelligent agent technologies-from straightforward Java implementations and practical agent applications to artificial intelligence algorithms

Constructing Intelligent Agents Using Java, Second Edition

Professional Developer's Guide

The Bigus team overhauls their bestselling guide to reflect changes in the Java platform and share the latest ideas in applied AI, software agents, and multiagent systems. The new edition continues to provide a comprehensive tutorial on the basic AI programming techniques and shows you how to design and develop practical intelligent agent applications in Java. You'll learn how to build agents that filter information from the Web, automate tasks, monitor dynamic Web content such as airfare information, and negotiate transactions in electronic marketplaces. You'll also construct a flexible agent platform where multiple agents can reside and interact on your PC.

Explore how this exciting new edition:
* Updates all code to support Java 2 and the Swing GUI
* Adds genetic algorithms and fuzzy rule system implementations
* Updates and expands the treatment of agents and multiagent systems
* Enhances the CIAgent framework with built-in timer and asynchronous event processing capabilities and use of the JavaBean component model
* Includes UML diagrams for the CIAgent classes and object interactions
* Provides a flexible agent platform where you can plug in your own agents
* Expands end-of-chapter exercises, Web resources, and bibliography

The CD-ROM contains:
* The complete Java code with JavaDocs for the examples in the book
* IBM Agent Building and Learning Environment (ABLE)
* Sun Microsystems' Java Run-Time Environment (JRE) 1.3

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Introduction

In this chapter, we present an introduction to the two major topics covered in this book: artificial intelligence (AI) and intelligent agents. We trace the history of AI research and discuss the basic premises of both the symbol processing and neural network schools. We explore the evolution of AI systems from a promising but largely discredited technology into the basis for today's intelligent agent applications. The simultaneous emergence of network computing and the Web, and their requirements for intelligent software are also discussed. We present key attributes of intelligent agents such as autonomy, mobility, and intelligence and provide a taxonomy for classifying various intelligent agent applications. We also discuss the unique features of the Java programming language that support our agent requirements. Artificial Intelligence

The science of AI is approximately forty years old, dating back to a conference held at Dartmouth in 1958. During the past forty years, the public perception of AI has not always matched the reality. In the early years, the excitement of both scientists and the popular press tended to overstate the real-world capabilities of AI systems. Early success in game playing, mathematical theorem proving, common-sense reasoning, and college mathematics seemed to promise rapid progress toward practical machine intelligence. During this time, the fields of speech recognition, natural language understanding, and image optical character recognition all began as specialties in AI research labs.

However, the early successes were followed by a slow realization that what was hard for people and easy for computers was more than offset by the things that were easy for people to do but almost impossible for computers to do. The promise of the early years has never been fully realized, and AI research and the term artificial intelligence have become associated with failure and over-hyped technology.

Nevertheless, researchers in AI have made significant contributions to computer science. Many of today's mainstream ideas about computers were once considered highly controversial and impractical when first proposed by the AI community. Whether it is the WIMP (windows, icon, mouse, pointer) user interface, which dominates human computer interaction today, or object-oriented programming techniques, which are sweeping commercial software development, AI has made an impact. Today, the idea of intelligent software agents helping users do tasks across networks of computers would not even be discussed if not for the years of research in distributed AI, problem solving, reasoning, learning, and planning. So before we dive into the tools and tricks of the AI trade, let's take a brief look at the underlying ideas behind the intelligence in our intelligent agents.

Basic Concepts

Throughout its history, AI has focused on problems that lie just beyond the reach of what state-of-the-art computers could do at that time [Rich and Knight 1991]. As computer science and computer systems have evolved to higher levels of functionality, the areas that fall into the domain of AI research have also changed. Invented to compute ballistics charts for World War II-era weapons, the power and versatility of computers were just being imagined. Digital computers were a relatively new concept, and the early ideas of what would be useful AI functions included game playing and mathematics.

After 40 years of work, we can identify three major phases of development in AI research. In the early years, much of the work dealt with formal problems that were structured and had well-defined problem boundaries. This included work on math related skills such as proving theorems, geometry, calculus, and playing games such as checkers and chess. In this first phase, the emphasis was on creating general "thinking machines" which would be capable of solving broad classes of problems. These systems tended to include sophisticated reasoning and search techniques.

A second phase began with the recognition that the most successful Al projects were aimed at very narrow problem domains and usually encoded much specific knowledge about the problem to be solved. This approach of adding specific domain knowledge to a more general reasoning system led to the first commercial success in AI: expert systems. Rule-based expert systems were developed to do various tasks including chemical analysis, configuring computer systems, and diagnosing medical conditions in patients. They utilized research in knowledge representation, knowledge engineering, and advanced reasoning techniques, and proved that AI could provide real value in commercial applications. At the same time, computer workstations were developed specifically to run Lisp, Prolog, and Smalltalk applications. These AI workstations featured powerful integrated development environments and were years ahead of other commercial software environments.

We are now well into a third phase of AI applications. Since the late 1980s, much of the AI community has been working on solving the difficult problems of machine vision and speech, natural language understanding and translation, common-sense reasoning, and robot control. A branch of AI known as connectionism regained popularity and expanded the range of commercial applications through the use of neural networks for data mining, modeling, and adaptive control. Biological methods such as genetic algorithms and alternative logic systems such as fuzzy logic have combined to reenergize the field of AI. Recently, the explosive growth in the Internet and distributed computing has led to the idea of agents that move through the network, interacting with each other and performing tasks for their users. Intelligent agents use the latest AI techniques to provide autonomous, intelligent, and mobile software agents, thereby extending the reach of users across networks.

Details zur Ausgabe

• Verlag: John Wiley & Sons
• Erscheinungsdatum: 2001
• Sprache: Englisch
• ISBN 10: 047139601X
• ISBN 13: 9780471396017
• Einband: Taschenbuch
• Auflage: 2
• Anzahl der Seiten: 410
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Buchpark GmbH; gpsr@buchpark.de; ; Krügerweg 1; Trebbin; Brandenburg; 14959; Deutschland