2010
DOI: 10.1007/978-3-642-11467-0_21
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Abstract: Summary. In the framework of cell-like membrane systems it is well known that the construction of exponential number of objects in polynomial time is not enough to efficiently solve NP-complete problems. Nonetheless, it may be sufficient to create an exponential number of membranes in polynomial time. In the framework of recognizer polarizationless P systems with active membranes, the construction of an exponential workspace expressed in terms of number of membranes and objects may not suffice to efficiently s… Show more

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Cited by 22 publications
(18 citation statements)
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References 11 publications
(6 reference statements)
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“…In [31], it was shown that the class of decision problems solvable in polynomial time by means of families of tissue P systems with cell division and symport rules with length 1 is equal to class P. Bearing in mind that systems from TSEC(1, ) are noncooperative ones, the dependency graph technique used in the cited paper can be used to obtain the result, in a similar way. TSEC(3, 2).…”
Section: Theoremmentioning
confidence: 99%
See 1 more Smart Citation
“…In [31], it was shown that the class of decision problems solvable in polynomial time by means of families of tissue P systems with cell division and symport rules with length 1 is equal to class P. Bearing in mind that systems from TSEC(1, ) are noncooperative ones, the dependency graph technique used in the cited paper can be used to obtain the result, in a similar way. TSEC(3, 2).…”
Section: Theoremmentioning
confidence: 99%
“…It was shown that in the framework of tissue P systems with cell division, only tractable problems can be efficiently solved by using communication rules with length at most one [31] (the length of such a rule is the total number of objects involved in it), but a uniform polynomial time solution to the HAM-CYCLE problem by a family of such P systems using communication rules with length at most two has been given [30]. On the other hand, in the framework of tissue P systems with cell separation, by using communication rules with length at most two, only tractable problems can be efficiently solved, but the SAT problem can be solved by this kind of P systems using communication rules with length at most three [26].…”
Section: Introductionmentioning
confidence: 99%
“…The dependency graph technique consists on the construction of a directed graph (dependency graph) G associated with a P system verifying the following: there exists an accepting computation of if and only if there exists a path between two distinguished nodes in the dependency graph associated with it (see [5] and [6] for more details). This property is verified by recognizer P systems with symport/antiport rules where all its communication rules are of length 1.…”
Section: Execution Stagementioning
confidence: 99%
“…Proof Let us recall that PMC TDC(1) = P (see [3] for details). Then, P ⊆ PMC TDC(1) ⊆ PMC TDC(1) = P.…”
Section: Computational Complexity Classes Of Tissue P Systems With Cementioning
confidence: 99%
“…On the one hand, it is well known that P = PMC TDC(1) [3]. On the other hand, in [15], a uniform and polynomial time solution of the HAM-CYCLE problem by a family of tissue P systems from TDC(2).…”
Section: Borderlines Of Efficiencymentioning
confidence: 99%