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Conference Papers Year : 2021

Optimising Attractor Computation in Boolean Automata Networks

Kévin Perrot
  • Function : Author
Sylvain Sené
  • Function : Author

Abstract

This paper details a method for optimising the size of Boolean automata networks in order to compute their attractors under the parallel update schedule. This method relies on the formalism of modules introduced recently that allows for (de)composing such networks. We discuss the practicality of this method by exploring examples. We also propose results that nail the complexity of most parts of the process, while the complexity of one part of the problem is left open.
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Dates and versions

hal-04440112 , version 1 (05-02-2024)

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Kévin Perrot, Pacôme Perrotin, Sylvain Sené. Optimising Attractor Computation in Boolean Automata Networks. LATA’20 & 21, Sep 2021, Milan, Italy. pp.68-80, ⟨10.1007/978-3-030-68195-1_6⟩. ⟨hal-04440112⟩
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