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Research on Modeling and Using Context Over 25 Years by Patrick Brézillon. [electronic resource] /

By: Material type: TextTextPublication details: Cham Springer Nature Switzerland 2023Edition: 1st ed. 2023Description: X, 62 p. 11 illus., 8 illus. in color. online resourceISBN:
  • 9783031393389
Subject(s): DDC classification:
  • 6.3
Online resources: Summary: This book is the outcome of 25 years of research on how to model and use context in real-world applications on a spectrum from technology-centered (SEPT, SART) to human-centered (e.g. FlexMIm) applications, that is, from well-defined domains to more fuzzy ones. It presents: · an operational definition of context that initiated a conceptual framework associated with an implementation framework, the Contextual-Graphs (CxG) formalism · the use of the research for designing a future type of AI systems, namely the context-based intelligent assistant systems There is a large international and interdisciplinary community of individuals convinced by the promises of bottom-up approaches as an alternative to the current top-down approaches in AI mainly. Practitioners will discover a tool easy to understand and use. Researchers will dispose of a comprehensive conceptual framework facilitating its extension on aspects not yet covered beyond group activity modeling, in the realm of the research on AI systems.
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Holdings
Item type Home library Call number Status Notes Date due Barcode Item holds
e-Book e-Book S. R. Ranganathan Learning Hub Online Available Platform:Springer EB2000
Total holds: 0

This book is the outcome of 25 years of research on how to model and use context in real-world applications on a spectrum from technology-centered (SEPT, SART) to human-centered (e.g. FlexMIm) applications, that is, from well-defined domains to more fuzzy ones. It presents: · an operational definition of context that initiated a conceptual framework associated with an implementation framework, the Contextual-Graphs (CxG) formalism · the use of the research for designing a future type of AI systems, namely the context-based intelligent assistant systems There is a large international and interdisciplinary community of individuals convinced by the promises of bottom-up approaches as an alternative to the current top-down approaches in AI mainly. Practitioners will discover a tool easy to understand and use. Researchers will dispose of a comprehensive conceptual framework facilitating its extension on aspects not yet covered beyond group activity modeling, in the realm of the research on AI systems.

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