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Intelligent Agents

Theory and Applications

  • Book
  • © 2004

Overview

Authors:
  1. Germano Resconi

    1. Department of Mathematics and Physics, Catholic University, Brescia, Italy

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  2. Lakhmi C. Jain

    1. Knowledge-Based Intelligent, Engineering Systems Centre, University of South Australia, Adelaide, Australia

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    You can also search for this author in PubMed   Google Scholar

  • Introduces new concepts in the area of intelligent agents

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 155)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xii
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  2. Evolutionary Adaptive Agents

    • Germano Resconi, Lakhmi C. Jain
    Pages 1-16

  3. Adaptive Agents and Their Actions

    • Germano Resconi, Lakhmi C. Jain
    Pages 17-79

  4. Abstract Theory of Adaptive Agents

    • Germano Resconi, Lakhmi C. Jain
    Pages 81-125

  5. Adaptive Agents and Complex Systems

    • Germano Resconi, Lakhmi C. Jain
    Pages 127-166

  6. Adaptive Agents and Models of the Brain Functions

    • Germano Resconi, Lakhmi C. Jain
    Pages 167-216

  7. Logic Actions of Adaptive Agents

    • Germano Resconi, Lakhmi C. Jain
    Pages 217-269

  8. The Hierarchical Structure of Adaptive Agents

    • Germano Resconi, Lakhmi C. Jain
    Pages 271-306

  9. The Adaptive Field in Logical Conceptual Space

    • Germano Resconi, Lakhmi C. Jain
    Pages 307-336

  10. Adaptive Agents in the Physical Domain

    • Germano Resconi, Lakhmi C. Jain
    Pages 337-375

  11. Practical Applications of Agents in Robots and Evolution Population

    • Germano Resconi, Lakhmi C. Jain
    Pages 377-399

  12. Back Matter

    Pages 401-402
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Keywords

About this book

This research book presents the agent theory and adaptation of agents in different contexts. Agents of different orders of complexity must be autonomous in the rules used. The agent must have a brain by which it can discover rules contained within the data. Because rules are the instruments by which agents change the environment, any adaptation of the rules can be considered as an evolution of the agents. Because uncertainty is present in every context, we shall describe in this book how it is possible to introduce global uncertainty from the local world into the description of the rules. This book contains ten chapters. Chapter 1 gives a general dscription of the evolutionary adaptation agent. Chapter 2 describes the actions and meta­ actions of the agent at different orders. Chapter 3 presents in an abstract and formal way the actions at different orders. Chapter 4 connects systems and meta systems with the adaptive agent. Chapter 5 describes the brain of the agent by the morphogenetic neuron theory. Chapter 6 introduces the logic structure of the adaptive agent. Chapter 7 describes the feedback and hyper-feedback in the adaptive agent. Chapter 8 introduces the adaptation field into the modal logic space as logic instrument in the adaptive agent. Chapter 9 describes the action of the agent in the physical domain. Chapter 10 presents the practical application of agents in robots and evolutionary computing.

Authors and Affiliations

  • Department of Mathematics and Physics, Catholic University, Brescia, Italy

    Germano Resconi

  • Knowledge-Based Intelligent, Engineering Systems Centre, University of South Australia, Adelaide, Australia

    Lakhmi C. Jain

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