Accepting networks of splicing processors: Complexity results

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In this paper we consider a new, bio-inspired computing model: the accepting network of splicing processors. We define two computational complexity classes based on this model and show how they are related to the classical ones defined for Turing machines, namely NP and PSPACE. Furthermore, we approach the topic of problem solving using these newly defined devices. In this context, a linear time solution for one of the most interesting NP-complete problems, the SAT problem, is presented. The results presented here suggest once more that nondeterminism might be approached in a deterministic way by means of multiplicities. © 2006 Elsevier Ltd. All rights reserved.




Manea, F., Martín-Vide, C., & Mitrana, V. (2007). Accepting networks of splicing processors: Complexity results. Theoretical Computer Science, 371(1–2), 72–82.

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