A framework for knowledge-based temporal abstraction

DOI10.1016/S0004-3702(96)00025-2zbMath1017.03517OpenAlexW2016449808MaRDI QIDQ1402747

Yuval Shahar

Publication date: 28 August 2003

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0004-3702(96)00025-2

zbMATH Keywords

Knowledge acquisitionKnowledge representationTemporal reasoningTemporal abstraction

Mathematics Subject Classification ID

Logic in artificial intelligence (68T27) Logics of knowledge and belief (including belief change) (03B42) Knowledge representation (68T30) Logic in computer science (03B70)

Related Items (10)

A generalized time quantifier approach to approximate reasoning ⋮ Learning short multivariate time series models through evolutionary and sparse matrix computation ⋮ Dynamical temporal interpretation contexts for temporal abstraction ⋮ \texttt{TIRPCLo}: efficient and complete mining of time intervals-related patterns ⋮ On the adoption of abductive reasoning for time series interpretation ⋮ A fuzzy constraint satisfaction approach for signal abstraction ⋮ Models of representation of fuzzy temporal knowledge in databases of temporal series ⋮ Knowledge-based temporal interpolation ⋮ Knowledge-based spatiotemporal linear abstraction ⋮ RESUME

Uses Software

• CLIPS
• Protege
• MOLE
• SALT

Cites Work

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• Towards a general theory of action and time
• Temporal logics in AI: semantical and ontological considerations
• Knowledge-based spatiotemporal linear abstraction
• Salt: A knowledge acquisition language for propose-and-revise systems
• Task modeling with reusable problem-solving methods

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