Tissue P Systems with Look-ahead Mode ∗

Tissue P systems are a class of distributed and parallel computing models inspired from inter-cellular communication and cooperation between cells. In this work, a variant of tissue P system, named tissue P sys- tem with look-ahead mode, is discussed for decreasing the inherent non-determinism of tissue P systems and help- ing implementing tissue P systems on computers. Such systems are proved to be universal by simulating register machine, and they are also proved to be able to efficiently solve computationally hard problems by means of a space- time tradeoff, which is illustrated with a polynomial solu- tion to 3-coloring problem.

[1]  Maurice Margenstern,et al.  On P systems with bounded parallelism , 2005, Seventh International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC'05).

[2]  Shuo Wang,et al.  Tissue P systems with cell separation: attacking the partition problem , 2010, Science China Information Sciences.

[3]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[4]  Sergey Verlan Look-Ahead Evolution for P Systems , 2009, Workshop on Membrane Computing.

[5]  Gheorghe Paun,et al.  Spiking Neural P Systems with Anti-Spikes , 2009, Int. J. Comput. Commun. Control.

[6]  Linqiang Pan,et al.  Spiking neural P systems: An improved normal form , 2010, Theor. Comput. Sci..

[7]  Gheorghe Paun,et al.  Spiking neural P systems with neuron division and budding , 2011, Science China Information Sciences.

[8]  Xiaolong,et al.  Uniform Solution to QSAT by P Systems with Proteins , 2012 .

[9]  S. Singer,et al.  The Fluid Mosaic Model of the Structure of Cell Membranes , 1972, Science.

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

[11]  Xiangxiang Zeng,et al.  Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources , 2010, Theor. Comput. Sci..

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

[13]  Gheorghe Paun,et al.  Spiking Neural dP Systems , 2011, Fundam. Informaticae.

[14]  Xiangxiang Zeng,et al.  Small Universal Spiking Neural P Systems Working in Exhaustive Mode , 2011, IEEE Transactions on NanoBioscience.

[15]  Artiom Alhazov,et al.  Tissue P Systems with Antiport Rules and Small Numbers of Symbols and Cells , 2005, Developments in Language Theory.

[16]  LINQIANG PAN,et al.  Computation of Ramsey Numbers by P Systems with Active Membranes , 2011, Int. J. Found. Comput. Sci..

[17]  Xiangxiang Zeng,et al.  Time-Free Spiking Neural P Systems , 2011, Neural Computation.

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

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

[20]  Xiaolong,et al.  Degree of Spiking Neural P Systems Without Delay , 2012 .

[21]  Linqiang Pan,et al.  A Tissue P Systems Based Uniform Solution to Tripartite Matching Problem , 2011, Fundam. Informaticae.