Data Graphs with Incomplete Information (and a Way to Complete Them)

C. Areces, V. Cassano, D. Dutto, and R. Fervari. Data Graphs with Incomplete Information (and a Way to Complete Them). In S. Gaggl, M. Martinez, and M. Ortiz, editors, Logics in Artificial Intelligence. 18th European Conference, JELIA 2023, Dresden, Germany, September 20–22, 2023, Proceedings, Lecture Notes in Computer Science, pp. 729–744, 2023.

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Abstract

We introduce a modal language for reasoning about data graphs with incomplete information. Such data graphs are formally represented as models in which data value functions are partial to capture what is unknown. In this setting, we also allow for unknown data values to be learned. Our main result is a sound and strongly complete axiomatization for the logic.

BibTeX

@InCollection{arec:data23,
  author =       "C. Areces and V. Cassano and D. Dutto and R. Fervari",
  title =        "Data Graphs with Incomplete Information (and a Way to
                 Complete Them)",
  editor = "S. Gaggl and M. Martinez and M. Ortiz",
  booktitle =    "Logics in Artificial Intelligence.  18th European
                  Conference, JELIA 2023, Dresden, Germany, September
                  20–22, 2023, Proceedings",
  year =         "2023",
  ISBN = {978-3-031-43618-5},
  series = {Lecture Notes in Computer Science},
  pages = {729-744},
  abstract =     "We introduce a modal language for reasoning about data
                 graphs with incomplete information. Such data graphs
                 are formally represented as models in which data value
                 functions are partial to capture what is unknown. In
                 this setting, we also allow for unknown data values to
                 be learned. Our main result is a sound and strongly
                 complete axiomatization for the logic.",
}