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Membrane Computing Aggregation (MCA): An Upgraded Framework for Transition P-Systems

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Bio-inspired Information and Communication Technologies (BICT 2019)

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Abstract

MCA (Membrane computing aggregation is experimental computational frame. It is inspired by the inner properties of membrane cells (Bio-inspired system). It is capable of problem solving activities by maintaining a special, “meaningful” relationship with the internal/external environment, integrating its self-reproduction processes within the information flow of incoming and outgoing signals. Because these problem solving capabilities, MCA admits a crucial evolutionary tuning by mutations and recombination of theoretical genetic “bridges” in a so called “aggregation” process ruled by a hierarchical factor that enclosed those capabilities. Throughout the epigenetic capabilities and the cytoskeleton and cell adhesion functionalities, MCA model gain a complex population dynamics specifics and high scalability. Along its developmental process, it can differentiate into meaningful computational tissues and organs that respond to the conditions of the environment and therefore “solve” the morphogenetic/configurational problem. MCA, above all, represents the potential for a new computational paradigm inspired in the higher level processes of membrane cells, endowed with quasi universal processing capabilities beyond the possibilities of cellular automata of and agent processing models.

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Author information

Authors and Affiliations

  1. Computer Science, Troy University, Troy, USA

    Alberto Arteta & Yanjun Zhao

  2. Computer Science, Polytechnic University of Madrid, Crtra Valencia km 7, Madrid, Spain

    Luis Fernando Mingo & Nuria Gomez

Authors
  1. Alberto Arteta
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  2. Luis Fernando Mingo
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  3. Nuria Gomez
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  4. Yanjun Zhao
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Corresponding author

Correspondence to Alberto Arteta .

Editor information

Editors and Affiliations

  1. Stefens Institute of Technology USA, Hoboken, NJ, USA

    Adriana Compagnoni

  2. Carnegie Mellon University, Pittsburgh, PA, USA

    William Casey

  3. Cylab, Carnegie Mellon University, Pittsburgh, PA, USA

    Yang Cai

  4. New York University, New York, NY, USA

    Bud Mishra

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Arteta, A., Mingo, L.F., Gomez, N., Zhao, Y. (2019). Membrane Computing Aggregation (MCA): An Upgraded Framework for Transition P-Systems. In: Compagnoni, A., Casey, W., Cai, Y., Mishra, B. (eds) Bio-inspired Information and Communication Technologies. BICT 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 289. Springer, Cham. https://doi.org/10.1007/978-3-030-24202-2_15

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  • DOI: https://doi.org/10.1007/978-3-030-24202-2_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24201-5

  • Online ISBN: 978-3-030-24202-2

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