DocumentCode
2967847
Title
Algorithm for Application of Evolution Rules Based on Linear Diofantic Equations
Author
Arteta, Alberto ; Fernandez, Luis ; Gil, Javier
Author_Institution
Natural Comput. Group, Univ. Politec. de Madrid, Madrid, Spain
fYear
2008
fDate
26-29 Sept. 2008
Firstpage
496
Lastpage
500
Abstract
Transition P system are a parallel and distributed computational model based on the notion of the cellular membrane structure. Each membrane determines a region that encloses a multiset of objects and evolution rules. Transition P systems evolve through transitions between two consecutive configurations. Moreover, transitions between two consecutive configurations are provided by an exhaustive non-deterministic and parallel application of evolution rules inside each membrane of the P system. Hence, rules application is critical for the whole evolution process efficiency, because it is performed in parallel inside each membrane in each one of the evolution steps. It is known that P systems have a high degree of nondeterminism and parallelism. A transition in such a system consists in applying in parallel a set of atomic actions (e.g., evolution rules) and this set of atomic actions is randomly chosen from a domain of possible next transitions. This paper tries to characterize this domain as the hyperspace defined by a set of diophantine equations and then to develop an algorithm which randomly chooses solutions from this hyperspace. Those solutions are uniquely related to the number of times that certain evolution rules are applied. The work presented here includes an algorithm based on resolving linear systems equations and explain into detail the process that the algorithm must follow.
Keywords
biocomputing; cellular biophysics; geometry; linear matrix inequalities; parallel algorithms; set theory; atomic action set; cellular membrane structure; distributed computational model; evolution rule set; exhaustive nondeterministic application; geometry; hyperspace domain; linear diofantic equation; linear matrix inequality; membrane computing; object multiset; parallel algorithm; parallel computational model; transition P system; Application software; Biological system modeling; Biology computing; Biomembranes; Computational modeling; Concurrent computing; Equations; Evolution (biology); Linear systems; Parallel processing; Evolution rules application; Natural Computing; Transition P system;
fLanguage
English
Publisher
ieee
Conference_Titel
Symbolic and Numeric Algorithms for Scientific Computing, 2008. SYNASC '08. 10th International Symposium on
Conference_Location
Timisoara
Print_ISBN
978-0-7695-3523-4
Type
conf
DOI
10.1109/SYNASC.2008.31
Filename
5204860
Link To Document