Learning Qualitative Differential Equation models

a survey of algorithms and applications

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Over the last two decades, qualitative reasoning (QR) has become an important domain in Artificial Intelligence. QDE (Qualitative Differential Equation) model learning (QML), as a branch of QR, has also received an increasing amount of attention; many systems have been proposed to solve various significant problems in this field. QML has been applied to a wide range of fields, including physics, biology and medical science. In this paper, we first identify the scope of
this review by distinguishing QML from other QML systems, and then review all the noteworthy QML systems within this scope. The applications of QML in several application domains are also introduced briefly. Finally, the future directions of QML are explored from different perspectives.
Original languageEnglish
Pages (from-to)69-107
Number of pages39
JournalKnowledge Engineering Review
Volume25
Issue number1
DOIs
Publication statusPublished - Mar 2010

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Differential equations
Learning systems
Artificial intelligence
Physics

Cite this

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title = "Learning Qualitative Differential Equation models: a survey of algorithms and applications",
abstract = "Over the last two decades, qualitative reasoning (QR) has become an important domain in Artificial Intelligence. QDE (Qualitative Differential Equation) model learning (QML), as a branch of QR, has also received an increasing amount of attention; many systems have been proposed to solve various significant problems in this field. QML has been applied to a wide range of fields, including physics, biology and medical science. In this paper, we first identify the scope of this review by distinguishing QML from other QML systems, and then review all the noteworthy QML systems within this scope. The applications of QML in several application domains are also introduced briefly. Finally, the future directions of QML are explored from different perspectives.",
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