Abstract
A neural implementation which provides an interesting massively parallel model for computing a fixed-point semantics of a program is introduced for multiadjoint logic programming [3]. Distinctive features of this programming paradigm are that: very general aggregation connectives in the bodies are allowed; by considering different adjoint pairs, it is possible to use several implications in the rules.
Partially supported by Spanish DGI project BFM2000-1054-C02-02.
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J. Medina, M. Ojeda-Aciego, and P. Vojtáš. Multi-adjoint logic programming with continuous semantics. In Logic Programming and Non-Monotonic Reasoning, LP-NMR’01, pages 351–364. Lect. Notes in Artificial Intelligence 2173, 2001.
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Medina, J., Mérida-Casermeiro, E., Ojeda-Aciego, M. (2002). Multi-adjoint Logic Programming: A Neural Net Approach. In: Stuckey, P.J. (eds) Logic Programming. ICLP 2002. Lecture Notes in Computer Science, vol 2401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45619-8_33
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DOI: https://doi.org/10.1007/3-540-45619-8_33
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