Abstract
The framework of multi-adjoint logic programming has shown to cover a number of approaches to reason under uncertainty, imprecise data or incomplete information. In previous works, we have presented a neural implementation of its fix-point semantics for a signature in which conjunctors are built as an ordinal sum of a finite family of basic conjunctors (Gödel and Łukasiewicz t-norms). Taking into account that a number of approaches to reasoning under uncertainty consider the set of subintervals of the unit interval as the underlying lattice of truth-values, in this paper we pursue an extension of the previous approach in order to accomodate calculation with truth-intervals.
Partially supported by Spanish DGI project TIC2003-09001-C02-01.
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Medina, J., Mérida-Casermeiro, E., Ojeda-Aciego, M. (2005). Interval-Valued Neural Multi-adjoint Logic Programs. In: Mira, J., Álvarez, J.R. (eds) Mechanisms, Symbols, and Models Underlying Cognition. IWINAC 2005. Lecture Notes in Computer Science, vol 3561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499220_53
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DOI: https://doi.org/10.1007/11499220_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26298-5
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