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2 Fundamenta Informaticae

2 2007

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Modelling Grammar Systems by Tissue P Systems Working in the Sequential Mode

Freund R., Oswald M.

Fundamenta Informaticae

2007

Vol. 76, nr 3

305-323

We consider tissue P systems where rules are applied when moving through a channel from one cell to another one. In a very general manner (i.e., working on arbitrary objects as strings, arrays, graphs, etc.), these tissue P systems equipped with the sequential derivation mode allow for the representation of hybrid co-operating grammar systems using the classic basic derivation modes *,t and ? k,=k, ^(3) k, for k ^(3) 1, as well as the internally hybrid modes ( ^(3) kU` ? l), for k,l Î \mathbbN , k ? l, and (tU` ? k) , ( tU` = k) , (tU` ^(3) k) , for k ^(3) 1. Moreover, we also show how these tissue P systems working in the sequential mode allow for the simulation of random context grammars, too.

Cooperating Distributed Grammar Systems as Models of Distributed Problem Solving, Revisited

Bordihn H., Holzer M.

Fundamenta Informaticae

2007

Vol. 76, nr 3

255-270

Based on a derivation mode f for cooperating distributed (CD) grammar systems, we introduce a new form of cooperation protocol, the so called "cut-f-mode" of derivation. Intuitively, in the cut-f-mode of derivation the sentential form is partitioned (cut) into several subwords, where some of these subwords are distributed to the components, which derive them according to the underlying f-mode of derivation, and finally the new sentential form is obtained by concatenating all the subwords-derived or not-in their original order. According to the original motivation from distributed artificial intelligence, the new functioning mode appears to be more realistic than the original model. We investigate the cut-mode versions of the basic derivation modes and some of their combined versions. It turns out that in most cases, the cut-f-mode is at most as powerful as the corresponding non-cut-mode, that is, the f-mode itself. In some cases the power is even reduced to that of context-free grammars.