Membrane Computing

Name: Membrane Computing | 11th International Conference, CMC 2010, Jena, Germany, August 24-27, 2010. Revised Selected Papers
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11th International Conference, CMC 2010, Jena, Germany, August 24-27, 2010. Revised Selected Papers

Marian Gheorghe Thomas Hinze Gheorghe Paun Grzegorz Rozenberg Arto Salomaa(Herausgeber*in)

Springer (Verlag)

Erschienen am 18. Januar 2011

IX, 393 Seiten

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Inhalt

Title
Preface
Table of Contents
Keynote Presentations
Membrane Computing at Twelve Years
References
Testing Based on P Systems - An Overview
Introduction
Grammar Based Methods
Finite State Machine Based Methods
Generating Test Sets Using Model Checking
Conclusions
References
Invited Presentations
Mobility in Computer Science and in Membrane Systems
Mobility in Process Calculi
Mobility in Membrane Computing
Conclusion
References
Organization Oriented Chemical Computing
Cellular Automata and the Quest for Nontrivial Artificial Self-Reproduction
Introduction
Cellular Automata
Von Neumann's Universal Constructor
The Notion of Nontrivial Self-Reproduction
Von Neumann's Cellular Automaton
Trivial versus Nontrivial Self-Reproduction
Self-Reproducing Loop Cellular Automata
Reproduction of Arbitrary Configurations
Concluding Remarks
References
An Algorithmic Approach to Tilings of Hyperbolic Spaces: 10 Years Later
Poincaré's Disc
The Pentagrid
Generalizations
The Heptagrid and the Tilings {p,4} and {p+2,3}, p5
The Splitting Method and the Tilings {p,q}
The Dodecagrid and the 120-Grid
The Tiling Problem
Cellular Automata in Hyperbolic Spaces
General Results
Complexity Results
Universality Results
Possible Applications
What Was Already Performed
What Could Be Done
References
Regular Presentations
Flattening the Transition P Systems with Dissolution
Introduction
P Systems and Multisets
A Simple Semantics of P Systems
Flattening Membrane Systems with Dissolution
Conclusion
References
The Family of Languages Generated by Non-cooperative Membrane Systems
Introduction
Definitions
Formal Language Preliminaries
Transitional P Systems
Context-Free Grammars and Time-Yield
The Membrane Family via the Derivation Trees of Context-Free Grammars
Comparison with Known Families
Closure Properties
A Difficult Language
Conclusions
References
Polymorphic P Systems
Introduction
What Is Implicitly Required in Most ``Practical" Problems?
Program is Data. Cell Nucleus
Definitions
Results
Discussion
References
A Small Universal Splicing P System
Introduction
Definitions
Splicing Operations
Splicing (Tissue) P Systems
Universal Restricted Splicing Tissue P System of Small Size
Conclusions
References
Membrane Systems Working in Generating and Accepting Modes: Expressiveness and Encodings
Introduction
Membrane Systems with Promoters
Definition
Membrane Systems and Multiset Languages
Results on Expressive Power and Encodings
Conclusions
References
BioSimWare: A Software for the Modeling, Simulation and Analysis of Biological Systems
Introduction
Modeling Biological Systems with BioSimWare
Compartmentalization
Species and Reactions
Stochastic Simulations Algorithms for Single and Multi-volume Systems
Single Volume Stochastic Simulation Algorithms
Multi-volume Stochastic Simulation Algorithms
Tools for the Analysis of Stochastic Simulations
Parameter Estimation
Other Analysis Tools
Applications
The Schlögl System
The Brussellator
Stiff Systems
Bacterial Chemotaxis
Simulation of Fredkin Circuits by Chemical Reaction Systems
Conclusion
References
Modeling Population Growth of Pyrenean Chamois (Rupicapra p. pyrenaica) by Using P-Systems
Introduction
Pyrenean Chamois
A P System Based Modeling Framework
Model
A Software Tool for Simulation
Results
Conclusions
References
On Generalized Communicating P Systems with One Symbol
Introduction
Preliminaries
Main Results
Conclusions
References
A Faster P Solution for the Byzantine Agreement Problem
Introduction
Preliminaries
The EIG-Based Byzantine Agreement Algorithm
P Modules
Revised Byzantine Agreement Solution
Rules and Correctness
Rule Sequence for $\Psi_h$'s Cell $\psi_h$
Rule Sequences for $\Gamma_hf$
Rule Sequence for $\Gamma_hf$'s Cell $\gamma_'hf$
Rule Sequence for $\Gamma_hf$'s Cell '$\gamma_'hf$
Rule Sequence for $\Gamma_hf$'s Cell $\gamma_hf$
Module $\Pi_h$
Complexity
Conclusions and Open Problems
References
Computationally Complete Spiking Neural P Systems without Delay: Two Types of Neurons Are Enough
Introduction
Definitions
Spiking Neural P Systems
Results
Conclusions
References
P Systems and Unique-Sum Sets
Introduction
Basic Definitions
P Systems
Register Machines
Unique-Sum Sets
P Systems with Symport/Antiport
Purely Multi-catalytic P Systems
Final Remarks
References
An Integrated Approach to P Systems Formal Verification
Introduction
Basic Definitions and Preliminary Relationships
P Systems
Kripke Structures
Linear Temporal Logic (LTL)
Transformation-Communication P Systems and Kripke Structure
Transforming P Systems to NuSMV Specifications
Transformation-Communication P Systems to NuSMV Specifications
Asynchronous Transformation-Communication P Systems Mapped to NuSMV Specifications
P Systems with Electrical Charges Mapped to NuSMV Specifications
Formal Verification Using NuSMV
Conclusions
References
Using the SRSim Software for Spatial and Rule-Based Modeling of Combinatorially Complex Biochemical Reaction Systems
Rule-Based Modeling in Space
Spatial Aspects
Installing SRSim
Required Software
Compiling SRSim
Using the Software
An Exemplary System
Definition of the Rule System
Molecule and Template Geometry Files
The LAMMPS Input Script
The Tool ``createGeo''
Concluding Remarks
References
Depth-First Search with P Systems
Introduction
The N-Queens Problem
Searching Strategies
Depth-First Search with P Systems
Example
A New Solution for the N-Queens Problem
A Brief Overview of the Computation
Examples
Conclusions and Future Work
References
Towards Modelling of Reactive, Goal-Oriented and Hybrid Intelligent Agents Using P Systems
Introduction
A MAS Scenario Including Goal-Oriented Agents
Formal Modelling of MAS
Agents as Cells
Data Structures and Objects
Behaviours and Rewrite/Communication Rules
Priorities of Behaviours
Communication Links and Bond Making
Dynamic Structure and Cell Differentiation/Division/Death
Main Proposal
Conclusions and Open Issues
References
Goldbeter's Mitotic Oscillator Entirely Modeled by MP Systems
Introduction
MP Systems
The Log-Gain Principle of MP Systems
Statistical Distribution of Mitotic MP Models
Model Classification According to Descriptional Parameters
Analytical Forms of Mitotic MP Grammars
Conclusions
References
Modelling Spatial Heterogeneity and Macromolecular Crowding with Membrane Systems
Introduction
Spatial Heterogeneity and Macromolecular Crowding in Living Cells
Reaction-Diffusion Systems
Macromolecular Crowding
Classic Computational Approaches
Multi-volume Stochastic Simulation Algorithms Based on P Systems
Validation of the Diffusion Implemented with -DPP
A Popular Diffusion Equation: The Heat Equation
Comparison between -DPP and the Heat Equation
Macromolecular Crowding with S-DPP
Conclusions
References
Randomized Gandy-Paun-Rozenberg Machines
Introduction
Gandy-$Paun-Rozenberg Machines
Examples
Randomized Gandy-Paun-Rozenberg Machines and NP Complete Problems
Concluding Remarks
References
Feasibility of Organizations - A Refinement of Chemical Organization Theory with Application to P Systems
Introduction
Chemical Organization Theory
Preliminaries
Chemical Organizations
Feasibility
Definitions
Theorem
Feasibility in P Systems
Examples
Conclusions
References
P Systems with Elementary Active Membranes: Beyond NP and coNP
Introduction
Definitions
Solving a PP-Complete Problem
Encoding of Formulae
Solution to Sqrt-3SAT
Conclusions
References
Polynomial Complexity Classes in Spiking Neural P Systems
Introduction
Prerequisites
Spiking Neural P Systems
Unary versus Binary Input/Output
Recognizer SN P Systems
Descriptional Complexity and Size of SN P Systems
Families of Recognizer SN P Systems
Efficiency of Basic Classes of SN P Systems
Conclusion
References
Spiking Neural P Systems with Neuron Division
Introduction
SN P Systems with Neuron Division
Solving SAT
Conclusions and Remarks
References
Matrix Representation of Spiking Neural P Systems
Introduction
Spiking Neural P Systems
Matrix Representation of SN P Systems
Matrix Representation for WSN P Systems
Conclusions and Remarks
References
Author Index

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