ARTIFICIAL INTELLIGENCE AND ITS APPLICABILITY TO GEOGRAPHICAL PROBLEM SOLVING.

Artificial Intelligence (AI) may be regarded as an attempt to understand the processes of perception and reasoning that underlie successful problem-solving and to incorporate the results of this research in effective computer programs. At present, AI is largely a collection of sophisticated programm...

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Publicado en:Professional Geographer Vol. 36; no. 2; pp. 147 - 159
Autor principal: Smith, Terence R.
Formato: Artículo
Publicado: Taylor & Francis Ltd May84
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: ARTIFICIAL INTELLIGENCE AND ITS APPLICABILITY TO GEOGRAPHICAL PROBLEM SOLVING.
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        au: Smith, Terence R.
        affil: Professor of Geography, University of California, Santa Barbara, CA 93106
      su:
        Artificial intelligence
        Expert systems
        Geodatabases
        Geographic information systems
        Computer software
        Problem solving
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        subj:
          Artificial intelligence
          Expert systems
          Geodatabases
          Geographic information systems
          Computer software
          Problem solving
      keyword:
        cognitive modeling
        expert system
        geographical information processing
      ab: Artificial Intelligence (AI) may be regarded as an attempt to understand the processes of perception and reasoning that underlie successful problem-solving and to incorporate the results of this research in effective computer programs. At present, AI is largely a collection of sophisticated programming techniques. Many of these techniques are based on the premise that the manner in which knowledge is acquired. Organized, accessed and modified in both humans and machines provides the basis of ‘intelligent’ decision-making. The techniques of AI are applicable to a wide variety of geographical problems, including the modeling of individual and aggregate decision-making, and the construction of expert systems and ‘intelligent’ geographical information systems.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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