Merging First-Order Knowledge Using Dilation Operators

DOI10.1007/978-3-540-77684-0_11zbMath1138.68560OpenAlexW2120566556MaRDI QIDQ5445298

Nikos Gorogiannis, Anthony Hunter

Publication date: 4 March 2008

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-77684-0_11

Mathematics Subject Classification ID

Logic in artificial intelligence (68T27) Knowledge representation (68T30) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (8)

Morphologic for knowledge dynamics: revision, fusion and abduction ⋮ Morpho-logic from a topos perspective -- application to symbolic AI ⋮ Solving conflicts in information merging by a flexible interpretation of atomic propositions ⋮ Sum-based weighted belief base merging: from commensurable to incommensurable framework ⋮ Belief revision, minimal change and relaxation: A general framework based on satisfaction systems, and applications to description logics ⋮ Logic based merging ⋮ On some associations between mathematical morphology and artificial intelligence ⋮ Logical dual concepts based on mathematical morphology in stratified institutions: applications to spatial reasoning

Cites Work

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• Knowledgebase transformations
• \(\text{DA}^2\) merging operators
• Disjunctive merging: quota and Gmin merging operators
• Propositional distances and compact preference representation
• Implementing semantic merging operators using binary decision diagrams
• Distance semantics for belief revision
• On the Semantics of Arbitration
• Error Detecting and Error Correcting Codes
• Merging Information Under Constraints: A Logical Framework

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