Analysis of multi-interpretable ecological monitoring information: Lecture Notes in AI

F.M.T. Brazier; J. Engelfriet; J. Treur

Analysis of multi-interpretable ecological monitoring information: Lecture Notes in AI

F.M.T. Brazier, J. Engelfriet, J. Treur

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Abstract

In this paper logical techniques developed to formalise the analysis of multi-interpretable information, in particular belief set operators and selection operators, are applied to an ecological domain. A knowledge-based decision support system is

Original language	English
Title of host publication	Applications of Uncertainty Formalisms, 1455
Pages	303-324
Publication status	Published - 1998

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Applications of Uncertainty Formalisms, 1455, 303-324

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title = "Analysis of multi-interpretable ecological monitoring information: Lecture Notes in AI",

abstract = "In this paper logical techniques developed to formalise the analysis of multi-interpretable information, in particular belief set operators and selection operators, are applied to an ecological domain. A knowledge-based decision support system is",

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AU - Treur, J.

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AB - In this paper logical techniques developed to formalise the analysis of multi-interpretable information, in particular belief set operators and selection operators, are applied to an ecological domain. A knowledge-based decision support system is

M3 - Conference contribution

SP - 303

EP - 324

BT - Applications of Uncertainty Formalisms, 1455

ER -

Analysis of multi-interpretable ecological monitoring information: Lecture Notes in AI

Abstract

Bibliographical note

UN SDGs

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