Book on Engineering Intelligent Hybrid Multi-Agent Systems

Fri May 9 21:31:04 EDT 1997

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                            *** BOOK ANNOUNCEMENT ***

                   ENGINEERING INTELLIGENT HYBRID MULTI-AGENT SYSTEMS 

				      by

                          Rajiv Khosla and Tharam Dillon

This book is about building intelligent hybrid systems, problem solving, and software modeling. It is relevant to practioners  and researchers in the areas of 
intelligent hybrid systems, control systems, multi-agent systems, knowledge discovery and data mining, software engineering, and enterprise-wide systems modeling. The book in many ways is a synergy of all these areas. The book can also be used as a text or reference book for postgraduate students in intelligent 
hybrid systems, software engineering, and system modeling.

On the  intelligent  hybrid systems front, the book covers applications and 
design concepts related to fusion systems, transformation systems and 
combination systems. It describes industrial applications in these areas 
involving hybrid configurations of knowledge based systems, case-based 
reasoning, fuzzy systems, artificial neural networks, and genetic algorithms.

On the problem solving front, the book describes an architectural theory   for 
engineering intelligent associative hybrid multi-agent systems.   The 
architectural theory is described at the task structure level and the 
computational level. From an organizational context the problem solving 
architecture is not only relevant at the knowledge engineering 
layer for developing knowledge agents but also at the information engineering 
layer for developing information agents.

On  the software modeling front, the book describes the role of objects,  
agents and problem solving in knowledge engineering, information engineering, 
data engineering, and software modeling of intelligent hybrid systems.  Based 
on the concepts developed in the book, an enterprise-wide systems modeling 
framework is described to facilitate forward and backward integration of 
systems developed     in the knowledge, information, and data engineering 
layers of an organization. In the modeling process, agent oriented analysis, 
design, and reuse aspects of software engineering are also discussed.

The book consists of four parts:

Part I: introduces various  methodologies  and their hybrid  applications in the        industry.

Part II: describes a multi-agent architectural theory  of associative 
	 intelligent hybrid systems  at the task structure level and the 
	 computational level. It covers various aspects related to knowledge 
	 modeling of hybrid systems.

Part III: describes the software engineering aspects of the architecture. It 
	  does that by describing a real-time alarm processing application of 
	  the architecture.

Part IV: takes a boader view    of the various  concepts and theories developed
	 in Part II and III  of the book  respectively in terms of 
	 enterprise-wide systems modeling, multi-agent systems, control 
	 systems, and software engineering and reuse.

Part I  is described through  chapters 1, 2, 3, 4 and 5 respectively.

Part II is described through chapters 6, 7, and 8 respectively.

Part III is described through chapters 9, 10, 11, and 12 respectively.

Part IV is described through chapters 13 and 14 respectively.

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                          Summary of Table of  Contents

PART I: Methodologies and Applications

Chapter 1. Why Intelligent Hybrid Systems

1.1 Introduction
1.2 Evolution of Hybrid Systems 
1.3 Classes of Hybrid Systems
1.4 Summary 
Chapter References

Chapter 2. Methodologies
2.1 Introduction 
2.2 Expert Systems 
2.3 Artficial Neural Networks
2.4 Fuzzy Systems
2.5 Genetic Algorithms
2.6 Knowledge Discovery and Data Mining
2.7 Object-Oriented Methodology
2.8 Agents and Agent Architectures 
2.9 Summary 
Chapter References

Chapter 3. Intelligent Fusion and Transformation Systems

3.1 Introduction 
3.2 Fusion and Transformation
3.3 Neural Network Based Neuro-Symbolic Fusion and Transformation Systems 
3.4 Neural Network Based Neuro-Fuzzy Fusion and Transformation Systems
3.5 Recapitulation 
3.6 Genetic Algorithms Based Fusion and Transformation Systems
3.7 Summary
Chapter References

Chapter4. Intelligent Combination Systems

4.1 Introduction
4.2 Intelligent Combination Approaches
4.3 Neuro-Symbolic Combination Systems
4.4 Symbolic-Genetic Combination Scheduling System 
4.5 Neuro-Fuzzy Combination Systems 
4.6 Neuro-Fuzzy-Case Combination System 
4.7 Combination Approach Based Intelligent Hybrid Control Applications 
4.8 Summary 
Chapter References

Chapter 5. Knowledge Discovery, Data Mining and Hybrid Systems

5.1 Introduction 
5.2 KDD Process 
5.3 KDD Application in Forecasting
5.4 Financial Trading Application 
5.5 Learning Rules \& Knowledge Hierarchies in the LED Digit Domain 
5.6 Rule Extraction in Computer Network Diagnosis Application
5.7 Summary
Chapter References
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PART II: Problem Solving and Architectural Theory

Chapter 6. Association Systems - Task Structure Level Associative Hybrid 
           Architecture

6.1 Introduction
6.2 Various Perspectives Characterizing Problem Solving 
6.3 Task Structure Level Architecture
6.4 Some Observations 
6.5 Summary
Chapter References

Chapter 7. Intelligent Multi-Agent Hybrid Computational Architecture - Part I

7.1 Introduction 
7.2 Object-Oriented Model
7.3 Agent Model
7.4 Distributed Operating System Process Model
7.5 Computational Level Intelligent Multi-Agent Hybrid Distributed Architecture 
    (IMAHDA)
7.6 Agent Building Blocks of IMAHDA
7.7 Summary 
Chapter References

Chapter 8. Intelligent Multi-Agent Hybrid Computational Architecture - Part II

8.1 Introduction 
8.2 Communication in IMAHDA 
8.3 Concept Learning in IMAHDA
8.4 Underlying Training Problems with Neural Networks
8.5 Learning and IMAHDA
8.6 Learning Knowledge in IMAHDA 
8.7 Learning Strategy in IMAHDA 
8.8 Dynamic Analysis of IMAHDA
8.9 Comprehensive View of IMAHDA's Agents
8.10 Emergent Characteristics of IMAHDA
8.11 Summary 
Chapter References

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PART III: Software Engineering Aspects

Chapter 9. Alarm Processing - An Application of IMAHDA
9.1 Introduction 
9.2 Characteristics of the Problem 
9.3 Survey of Existing Methods
9.4 IMAHDA and Alarm Processing
9.5 Application of IMAHDA 
9.6 Summary 
Chapter References

Chapter 10. Agent Oriented Analysis and Design of the RTAPS - Part I
10.1 Introduction 
10.2 Agent Oriented Analysis (AOA) 
10.3 AOA of the RTAPS 
10.4 Summary 
Chapter References

Chapter 11. Agent Oriented Analysis and Design of the RTAPS - Part II
11.1 Introduction 
11.2 Agent Oriented Analysis Continued 
11.3 Agent Oriented Design of the RTAPS
11.4 Emergent Characteristics of the RTAPS Agents 
11.5 Summary 
Chapter References

Chapter 12. RTAPS Implementation
12.1 Introduction 
12.2 IMAHDA Related Issues 
12.3 Training of Neural Networks in RTAPS 
12.4 Power System Aspects of the RTAPS 
12.5 Scalability and Cost Effectiveness
12.6 Summary 
Chapter References

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PART IV: Software Modeling

Chapter 13. From Data Repositories to Knowledge Repositories - Intelligent                  Organizations
13.1 Introduction 
13.2 Information Systems and Organizational Levels
13.3 Characteristics of Information Systems 
13.4 Information Systems and Knowledge Systems
13.5 IMAHDA and Organizational Knowledge Systems 
13.6 Application of IMAHDA in Sales \& Marketing Function 
13.7 Unified Approach to Enterprise-Wide System Modeling 
13.8 Summary 
Chapter References

Chapter 14. IMAHDA Revisited
14.1 Introduction 
14.2 IMAHDA and Problem Solving 
14.3 IMAHDA and Hybrid Systems 
14.4 IMAHDA and Control Systems
14.5 IMAHDA and Multi-Agent Systems
14.6 IMAHDA and Software Engineering 
14.7 IMAHDA and Enterprise-wide Systems Modeling
Chapter References

Appendices

Index

The book consists of 412 pages and is being published in USA by
Kluwer Academic Publishers. For  ordering and other information, please contact

Alexander Greene
Publisher
Kluwer Academic Publishers
101 Philip Drive
Assinippi Park
Norwell, MA 02061
U.S.A
Phone: +1.617.8716600
Fax: +1.617.871.6528
E-Mail: agreene at wkap.com
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Dr Rajiv Khosla
School of Computer and Computer Engineering
La Trobe University
Melbourne, Victoria - 3083
Australia
Phone: +61.3.94793034
Fax: +61.3.94793060
E-Mail:khosla at cs.latrobe.edu.au