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An Integrated Conceptual Environment based on Collective Intelligence and Distributed Artificial Intelligence for Connecting People on Problem Solving

Author

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  • Vasile MAZILESCU

    (Faculty of Economics and Business Administration, Dunarea de Jos University of Galati, Romania)

Abstract

This paper aims to analyze the different forms of intelligence within organizations in a systemic and inclusive vision, in order to conceptualize an integrated environment based on Distributed Artificial Intelligence (DAI) and Collective Intelligence (CI). In this way we effectively shift the classical approaches of connecting people with people using collaboration tools (which allow people to work together, such as videoconferencing or email, groupware in virtual space, forums, workflow), of connecting people with a series of content management knowledge (taxonomies and documents classification, ontologies or thesauri, search engines, portals), to the current approaches of connecting people on the use (automatic) of operational knowledge to solve problems and make decisions based on intellectual cooperation. The best way to use collective intelligence is based on knowledge mobilization and semantic technologies. We must not let computers to imitate people but to support people think and develop their ideas within a group. CI helps people to think together, while DAI tries to support people so as to limit human error. Within an organization, to manage CI is to combine instruments like Semantic Technologies (STs), knowledge mobilization methods for developing Knowledge Management (KM) strategies, and the processes that promote connection and collaboration between individual minds in order to achieve collective objectives, to perform a task or to solve increasingly economic complex problems.

Suggested Citation

  • Vasile MAZILESCU, 2012. "An Integrated Conceptual Environment based on Collective Intelligence and Distributed Artificial Intelligence for Connecting People on Problem Solving," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 3, pages 61-70.
  • Handle: RePEc:ddj:fseeai:y:2012:i:3:p:61-70
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    File URL: http://www.ann.ugal.ro/eco/Doc2012.3/Mazilescu.pdf
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    References listed on IDEAS

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    1. G. Fagiolo & G. Dosi & R. Gabriele, 2004. "Matching, Bargaining, And Wage Setting In An Evolutionary Model Of Labor Market And Output Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 157-186.
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    More about this item

    Keywords

    CI; DAI; STs; KM;
    All these keywords.

    JEL classification:

    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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