Build your own intelligent agent system... Intelligent agent technology is a tool of modern computer science that can be used to engineer complex computer programmes that behave rationally in dynamic and changing environments. Applications range from small programmes that intelligently search the Web buying and selling goods via electronic commerce, to autonomous space probes. This powerful technology is not widely used, however, as developing intelligent agent software requires high levels of training and skill. The authors of this book have developed and tested a methodology and tools for developing intelligent agent systems. With this methodology (Prometheus) developers can start agent-oriented designs and implementations easily from scratch saving valuable time and resources. Developing Intelligent Agent Systems not only answers the questions “what are agents?” and “why are they useful?” but also the crucial question: “how do I design and build intelligent agent systems?” The book covers everything a practitioner needs to know to begin to effectively use this technology - including an introduction to the notion of agents, a description of the concepts involved, and a software engineering methodology. Read on for: a practical step-by-step introduction to designing and building intelligent agent systems. a full life-cycle methodology for developing intelligent agent systems covering specification, analysis, design and implementation of agents. PDT: Prometheus Design Tool – software support for the Prometheus design process. the example of an electronic bookstore to illustrate the design process throughout the book. Electronic resources including the Prometheus Design Tool (PDT), can be found at: http://www.cs.rmit.edu.au/agents/prometheus This book is aimed at industrial software developers, software engineers and at advanced undergraduate students. It assumes knowledge of basic software engineering but does not require knowledge of Artificial Intelligence or of mathematics. Familiarity with Java will help in reading the examples in chapter 10.

This monograph presents a comprehensive state-of-the-art survey on approaches to the design of intelligent agents. On the theoretical side, the author identifies a set of general requirements for autonomous interacting agents and provides an essential step towards understanding the principles of intelligent agents. On the practical side, the novel agent architecture InteRRaP is introduced: the detailed description and evaluation of this architecture is an ideal guideline and case study for software engineers or researchers faced with the task of building an agent system. The book uniquely bridges the gap between theory and practice; it addresses active and novice researchers as well as practitioners interested in applicable agent technology.

The first book to provide an integrative presentation of the issues, challenges and success of designing, building and using agent applications. The chapters presented are written by internationally leading authorities in the field, with a general audience in mind. The result is a unique overview of agent technology applications, ranging from an introduction to the technical foundations to reports on dealing with specific agent systems in practice.

From theoretical and practical viewpoints, the application of intelligent software agents is a topic of major interest. There has been a growing interest not only in new methodologies for development of intelligent software agents, but also the way in which these methodologies can be supported by theories and practice. Intelligent Agent Software Engineering focuses on addressing the theories and practices associated with implementing intelligent software agents.

Knowledge Mining Using Intelligent Agents explores the concept of knowledge discovery processes and enhances decision-making capability through the use of intelligent agents like ants, termites and honey bees. In order to provide readers with an integrated set of concepts and techniques for understanding knowledge discovery and its practical utility, this book blends two distinct disciplines data mining and knowledge discovery process, and intelligent agents-based computing (swarm intelligence and computational intelligence). For the more advanced reader, researchers, and decision/policy-makers are given an insight into emerging technologies and their possible hybridization, which can be used for activities like dredging, capturing, distributions and the utilization of knowledge in their domain of interest (i.e. business, policy-making, etc.). By studying the behavior of swarm intelligence, this book aims to integrate the computational intelligence paradigm and intelligent distributed agents architecture to optimize various engineering problems and efficiently represent knowledge from the large gamut of data.

Engineering Intelligent Hybrid Multi-Agent Systems is about building intelligent hybrid systems. Included is coverage of applications and design concepts related to fusion systems, transformation systems and combination systems. These applications are in areas involving hybrid configurations of knowledge-based systems, case-based reasoning, fuzzy systems, artificial neural networks, genetic algorithms, and in knowledge discovery and data mining. Through examples and applications a synergy of these subjects is demonstrated. The authors introduce a multi-agent architectural theory for engineering intelligent associative hybrid systems. The architectural theory is described at both the task structure level and the computational level. This problem-solving architecture is relevant for developing knowledge agents and information agents. An enterprise-wide system modeling framework is outlined to facilitate forward and backward integration of systems developed in the knowledge, information, and data engineering layers of an organization. In the modeling process, software engineering aspects like agent oriented analysis, design and reuse are developed and described. Engineering Intelligent Hybrid Multi-Agent Systems is the first book in the field to provide details of a multi-agent architecture for building intelligent hybrid systems.

Building Intelligent Agents is unique in its comprehensive coverage of the subject. The first part of the book presents an original theory for building intelligent agents and a methodology and tool that implement the theory. The second part of the book presents complex and detailed case studies of building different types of agents: an educational assessment agent, a statistical analysis assessment and support agent, an engineering design assistant, and a virtual military commander. Also featured in this book is Disciple, a toolkit for building interactive agents which function in much the same way as a human apprentice. Disciple-based agents can reason both with incomplete information, but also with information that is potentially incorrect. This approach, in which the agent learns its behavior from its teacher, integrates many machine learning and knowledge acquisition techniques, taking advantage of their complementary strengths to compensate for each others weakness. As a consequence, it significantly reduces (or even eliminates) the involvement of a knowledge engineer in the process of building an intelligent agent.