APCol systems with teams

Lucie Ciencialová, Luděk Cienciala, E. Csuhaj-Varjú

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We investigate the possibility of “going beyond” Turing in the terms of Automaton-like P Colonies (APCol systems, for short), variants of P colonies processing strings as their environments. We use the notion of teams of agents as a restriction for the maximal parallelism of the computation. In addition, we assign a colour to each team. In the course of the computation, the colour is changing according to the team that is currently active. We show that we can simulate red-green counter machines with APCol systems with two-coloured teams of minimal size. Red-green counter machines are computing devices with infinite run on finite input that exceed the power of Turing machines.

Original languageEnglish
Title of host publicationMembrane Computing - 18th International Conference, CMC 2017, Revised Selected Papers
PublisherSpringer Verlag
Pages88-104
Number of pages17
ISBN (Print)9783319733586
DOIs
Publication statusPublished - Jan 1 2018
Event18th International Conference on Membrane Computing, CMC 1018 - Bradford, United Kingdom
Duration: Jul 24 2017Jul 28 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10725 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Membrane Computing, CMC 1018
CountryUnited Kingdom
CityBradford
Period7/24/177/28/17

Keywords

  • APCol systems
  • Automaton-like P colonies
  • Red-green counter machine
  • Teams
  • Unbounded computation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Ciencialová, L., Cienciala, L., & Csuhaj-Varjú, E. (2018). APCol systems with teams. In Membrane Computing - 18th International Conference, CMC 2017, Revised Selected Papers (pp. 88-104). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10725 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-73359-3_6