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    This (lowercase (translateProductType product.productType)) has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Lekkas, G.P. Avouris, N.M. and Papakonstantinou, G.K. 1995. Development of distributed problem solving systems for dynamic environments. IEEE Transactions on Systems, Man, and Cybernetics, Vol. 25, Issue. 3, p. 400.

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  • Print publication year: 1993
  • Online publication date: August 2010

Towards a method for multi-agent system design

    • By A. Ovalle, Groupe SIC (Integrated Cognitive Systems) Equipe de Reconnaissance des Formes et de Microscopie Quantitative Laboratoire TIM3 - Institut IMAG Bât. CERMO - BP 53X - 38041 Grenoble Cedex, FRANCE, C. Grabay, Groupe SIC (Integrated Cognitive Systems) Equipe de Reconnaissance des Formes et de Microscopie Quantitative Laboratoire TIM3 - Institut IMAG Bât. CERMO - BP 53X - 38041 Grenoble Cedex, FRANCE
  • M. A. Bramer, University of Portsmouth, R. W. Milne
  • Publisher: Cambridge University Press
  • https://doi.org/10.1017/CBO9780511569944.007
  • pp 93-106
Summary

Abstract

We describe a method for Multi-Agent System design which is assisted by two original typologies, resulting from the deeper study of knowledge and reasoning. The first typology reflects a formal character while the second reflects a technological character. The purpose of the Formal Typology is the classification and structuring of knowledge and reasoning. The Technological Typology handles the parameters governing the reasoning intrinsic to Multi-Agent technology, not only at the individual level of the agent but also within a group of agents. Possible correspondence between both of these typologies will become concrete by the presentation of the Multi-Agent generator MAPS (Multi-Agent Problem Solver), and the Multi-Agent system KIDS (Knowledge based Image Diagnosis System) devoted to Biomedical Image Interpretation.

Keywords

Second Generation Expert Systems, Multi-Agent System Design, Distributed Artificial Intelligence, Knowledge and Reasoning Modeling, Control, Biomedical Image Interpretation.

INTRODUCTION

Among knowledge based systems using artificial intelligence techniques we are particularly interested in the Multi-Agent systems which arise from their second generation (systems using multiple reasoning schemes). The Multi-Agent paradigm results from distributed artificial intelligence approaches and makes it possible to overcome the drawbacks encountered during the resolution of complex problems. The main issue of the Multi-Agent approach involves the distribution of tasks and skills among intelligent entities that co-operate, pooling their knowledge and their expertise to attain an aim (Ferber 88). In this way, not only a multi-modal knowledge representation, and reasoning schemes handling are permitted but also, co-operative problem solving.

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Research and Development in Expert Systems IX
  • Online ISBN: 9780511569944
  • Book DOI: https://doi.org/10.1017/CBO9780511569944
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