Cell-Like P Systems With Channel States and Symport/Antiport Rules

Cell-like P systems with symport/antiport rules are inspired by the structure of a cell and the way of communicating substances through membrane channels between neighboring regions. In this work, channel states are introduced into cell-like P systems with symport/antiport rules, and we call this variant of communication P systems as cell-like P systems with channel states and symport/antiport rules. In such P systems, at most one channel is established between neighboring regions, each channel associates with one state in order to control communication at each step, and rules are used in a sequential manner: on each channel at most one rule can be used at each step. The computational power of such P systems is investigated. Specifically, we show that cell-like P systems with two states and using uniport rules, or with any number of states and using antiport rules of length two, are able to compute only finite sets of non-negative integers. We further prove that cell-like P systems with two membranes are as powerful as Turing machines when channel states and symport/antiport rules are suitably combined. The results show that channel states are a feature that can increase the computational power of cell-like P systems with symport/antiport rules.

[1]  Variants of Small Universal P Systems with Catalysts , 2015, Fundam. Informaticae.

[2]  Mario de Jesús Pérez Jiménez,et al.  Membrane fission versus cell division: When membrane proliferation is not enough , 2015 .

[3]  Artiom Alhazov Number of Protons/Bi-stable Catalysts and Membranes in P Systems. Time-Freeness , 2005, Workshop on Membrane Computing.

[4]  Marian Gheorghe,et al.  Evolutionary membrane computing: A comprehensive survey and new results , 2014, Inf. Sci..

[5]  Artiom Alhazov,et al.  Towards a Characterization of P Systems with Minimal Symport/Antiport and Two Membranes , 2006, Workshop on Membrane Computing.

[6]  Mario de Jesús Pérez Jiménez,et al.  Minimal Cooperation in P Systems with Symport/Antiport: A Complexity Approach , 2015 .

[7]  Linqiang Pan,et al.  Computational Efficiency and Universality of Timed P Systems with Membrane Creation , 2014, BIC-TA.

[8]  Marvin Minsky,et al.  Computation : finite and infinite machines , 2016 .

[9]  Pierluigi Frisco,et al.  Asynchronous P systems with active membranes , 2012, Theor. Comput. Sci..

[10]  Bosheng Song,et al.  Membrane fission: A computational complexity perspective , 2016, Complex..

[11]  Matteo Cavaliere,et al.  Time-Independent P Systems , 2004, Workshop on Membrane Computing.

[12]  Gheorghe Paun,et al.  Membrane Computing , 2002, Natural Computing Series.

[13]  Ferrante Neri,et al.  An Optimization Spiking Neural P System for Approximately Solving Combinatorial Optimization Problems , 2014, Int. J. Neural Syst..

[14]  Erzsébet Csuhaj-Varjú,et al.  On small universal antiport P systems , 2007, Theor. Comput. Sci..

[15]  Hong Peng,et al.  An unsupervised learning algorithm for membrane computing , 2015, Inf. Sci..

[16]  Gheorghe Paun Spiking Neural P Systems: A Tutorial , 2007, Bull. EATCS.

[17]  Andrei Paun,et al.  Computing by Communication in Networks of Membranes , 2002, Int. J. Found. Comput. Sci..

[18]  Mario de Jesús Pérez Jiménez,et al.  Characterizing tractability by tissue-like p systems , 2009 .

[19]  Linqiang Pan,et al.  Asynchronous spiking neural P systems with local synchronization , 2013, Inf. Sci..

[20]  Andrei Paun,et al.  The power of communication: P systems with symport/antiport , 2002, New Generation Computing.

[21]  Mario J Pérez-Jiménez,et al.  Efficient solutions to hard computational problems by P systems with symport/antiport rules and membrane division , 2015, Biosyst..

[22]  Giancarlo Mauri,et al.  On a Paun's Conjecture in Membrane Systems , 2007, IWINAC.

[23]  Hendrik Jan Hoogeboom,et al.  P systems with symport/antiport simulating counter automata , 2004, Acta Informatica.

[24]  Gheorghe Paun,et al.  Computing with Membranes , 2000, J. Comput. Syst. Sci..

[25]  Linqiang Pan,et al.  Computational efficiency and universality of timed P systems with active membranes , 2015, Theor. Comput. Sci..

[26]  Linqiang Pan,et al.  Time-free solution to SAT problem using P systems with active membranes , 2014, Theor. Comput. Sci..

[27]  Alfonso Rodríguez-Patón,et al.  Tissue P systems , 2003, Theor. Comput. Sci..

[28]  Linqiang Pan,et al.  A P_Lingua Based Simulator for P Systems with Symport/Antiport Rules , 2015, Fundam. Informaticae.

[29]  Rudolf Freund,et al.  Matrix Languages, Register Machines, Vector Addition Systems , 2005 .

[30]  Rudolf Freund,et al.  Tissue P systems with channel states , 2005, Theor. Comput. Sci..

[31]  Petr Sosík,et al.  An Optimal Frontier of the Efficiency of Tissue P Systems with Cell Separation , 2015, Fundam. Informaticae.

[32]  Rudolf Freund,et al.  P Systems with Activated/Prohibited Membrane Channels , 2002, WMC-CdeA.

[33]  Rudolf Freund,et al.  Membrane Systems with Symport/Antiport Rules: Universality Results , 2002, WMC-CdeA.

[34]  Linqiang Pan,et al.  Spiking neural P systems with request rules , 2016, Neurocomputing.

[35]  Andrei Paun,et al.  On the Universality of Axon P Systems , 2015, IEEE Transactions on Neural Networks and Learning Systems.

[36]  Artiom Alhazov,et al.  P Systems with One Membrane and Symport/Antiport Rules of Five Symbols Are Computationally Complete , 2005 .

[37]  Hong Peng,et al.  Fuzzy reasoning spiking neural P system for fault diagnosis , 2013, Inf. Sci..

[38]  Ivan Korec,et al.  Small Universal Register Machines , 1996, Theor. Comput. Sci..

[39]  Gabriel Ciobanu,et al.  P systems with minimal parallelism , 2007, Theor. Comput. Sci..

[40]  Mario J. Pérez-Jiménez,et al.  Computational complexity of tissue-like P systems , 2010, J. Complex..

[41]  Vincenzo Deufemia,et al.  Further results on time-free P systems , 2006, Int. J. Found. Comput. Sci..

[42]  Linqiang Pan,et al.  Limited Asynchronous Spiking Neural P Systems , 2011, Fundam. Informaticae.

[43]  Xiangrong Liu,et al.  The power of time-free tissue P systems: Attacking NP-complete problems , 2015, Neurocomputing.

[44]  Linqiang Pan,et al.  On the Universality and Non-Universality of Spiking Neural P Systems With Rules on Synapses , 2015, IEEE Transactions on NanoBioscience.

[45]  Artiom Alhazov,et al.  Symbol/Membrane Complexity of P Systems with Symport/Antiport Rules , 2005, Workshop on Membrane Computing.

[46]  Gheorghe Paun,et al.  Symport/Antiport P Systems with Three Objects Are Universal , 2004, Fundam. Informaticae.

[47]  Antoni Margalida,et al.  Application of a computational model for complex fluvial ecosystems: The population dynamics of zebra mussel Dreissena polymorpha as a case study , 2014 .