Last edited by Moogut
Friday, May 15, 2020 | History

8 edition of Fuzzy-Neuro Approach to Agent Applications found in the catalog.

Fuzzy-Neuro Approach to Agent Applications

by Raymond S.T. Lee

  • 99 Want to read
  • 22 Currently reading

Published by Springer .
Written in

    Subjects:
  • Artificial intelligence,
  • Neural networks (Computer science),
  • Fuzzy logic,
  • Computer Science,
  • Logic,
  • Computer Bks - General Information,
  • Computers - General Information,
  • Networking - General,
  • Computer Books: General,
  • Mathematics,
  • Intelligent agents (Computer software),
  • Artificial Intelligence - General,
  • Computers,
  • Ontology,
  • Chaos Theory,
  • Computers / Artificial Intelligence,
  • Intelligent Agents,
  • Neural Networks

  • The Physical Object
    FormatHardcover
    Number of Pages350
    ID Numbers
    Open LibraryOL9054593M
    ISBN 103540212035
    ISBN 109783540212034

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Fuzzy-Neuro Approach to Agent Applications by Raymond S.T. Lee Download PDF EPUB FB2

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Fuzzy-Neuro Approach to Agent Applications: From the AI Perspective to Modern Ontology (Springer Series on Agent Technology) th Edition, Kindle EditionManufacturer: Springer. The book provides a full explanation of the concepts and theories of intelligent agents and agent-based systems.

Providing a comprehensive theoretical background, the author covers modern artificial intelligence topics such as ontologies, neural networks, chaos theory, fuzzy logics and genetic algorithms.

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Fuzzy-neuro approach to agent applications: from the AI perspective to modern ontology. [R S T Lee] -- The book provides a full explanation of the Fuzzy-Neuro Approach to Agent Applications book and theories of intelligent agents and agent-based systems.

Part II - Applications of Intelligent Agents Using iJADK 5 The Design and Implementation of an Intelligent Agent-Based System Using iJADK Introduction iJADE- System Framework iJADE Architecture Application Layer Conscious (Intelligent) Layer Technology Layer Supporting Layer Fuzzy-neuro approach to agent applications: from the AI perspective to modern ontology.

[R S T Lee] Citations are based on reference standards. However, formatting rules can vary widely between applications and fields of interest or study.

The specific requirements or preferences of your reviewing publisher, classroom teacher, institution. Fishpond Singapore, Fuzzy-Neuro Approach to Agent Applications: From the aI Perspective to Modern Ontology (Springer Series on Agent Technology) by Raymond S T LeeBuy. Books online: Fuzzy-Neuro Approach to Agent Applications: From the aI Perspective to Modern Ontology (Springer Series on Agent Technology),Fuzzy-neuro approach to agent applications: from the AI perspective to modern ontology.

By RST Lee. Abstract. Department of Computing > Academic research: refereed > Research book or monograph (author Topics: Intelligent agents Author: RST Lee. Howard M. Schwartz, PhD, received his Degree from McGill University, Montreal, Canada in une and his MS Degree and PhD Degree from MIT, Cambridge, USA in and is currently a professor in systems and computer engineering at Carleton University, Canada.

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Neuro fuzzy applications in educational field are getting more and more popular during the last decade (–) and that is why much relevant research has been conducted. Neuro fuzzy system has a wide range of applications in the educational field and new directions are constantly given in educational by: Part of the Springer Series in Agent Technology book series (SSAT) Conclusion iJADE WShopper — Intelligent Mobile Shopping Based on Fuzzy-Neuro Shopping Agents.

In: Fuzzy-Neuro Approach to Agent Applications. Springer Series in Agent. the academia but also in industrial applications. Neuro-fuzzy modeling can be regarded as a gray-box technique on the boundary between neural networks and qualitative fuzzy models. The tools for building neuro-fuzzy models are based on combinations of algorithms from the fields of neural networks, pattern recognition and regression Size: KB.

This paper presents a novel system using a neuro-fuzzy based agent approach for automatically determining the key skill characteristics defining each expert's preferences and ranking decisions. On the basis of known models of neuro- fuzzy agents are proposed a model of the fundamental intelligent agent (FIA), operating in a dynamic heterogeneous information environment and carrying out reception of input messages in a usual source language and fuzzy input language, the creation of messages in the inner language to perform reasoning and Cited by: 3.

Neuro-Fuzzy and Soft Computing provides the first comprehensive treatment of the constituent methodologies underlying neuro-fuzzy and soft computing, an evolving branch of computational intelligence. The constituent methodologies include fuzzy set theory, neural networks, data clustering techniques, and several stochastic optimization methods that do not require gradient Reviews: 1.

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