Abstract
We present in this paper a neural-like membrane system solving the SAT problem in linear time. These neural Psystems are nets of cells working with multisets. Each cell has a finite state memory, processes multisets of symbol-impulses, and can send impulses (“excitations”) to the neighboring cells. The maximal mode of rules application and the replicative mode of communication between cells are at the core of the eficiency of these systems.
Work partially supported by the Spanish Ministry of Science and Technology under Project TIC2002-04220-C03-03.
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Pazos, J., Rodríguez-Patón, A., Silva, A. (2003). Solving SAT in Linear Time with a Neural-like Membrane System. In: Mira, J., Álvarez, J.R. (eds) Computational Methods in Neural Modeling. IWANN 2003. Lecture Notes in Computer Science, vol 2686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44868-3_84
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DOI: https://doi.org/10.1007/3-540-44868-3_84
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