Generalised Stream X-Machines and Cooperating Distributed Grammar Systems

Author:

Gheorghe Marian1

Affiliation:

1. Department of Computer Science, Sheffield University, Sheffield, UK, , , , , , GB

Abstract

Abstract. Stream X-machines are a general and powerful computational model. By coupling the control structure of a stream X-machine with a set of formal grammars a new machine called a generalised stream X-machine with underlying distributed grammars , acting as a translator, is obtained. By introducing this new mechanism a hierarchy of computational models is provided. If the grammars are of a particular class, say regular or context-free, then finite sets are translated into finite sets, when ? k , = k derivation strategies are used, and regular or context-free sets, respectively, are obtained for ? k , * and terminal derivation strategies. In both cases, regular or context-free grammars, the regular sets are translated into non-context-free languages. Moreover, any language accepted by a Turing machine may be written as a translation of a regular set performed by a generalised stream X-machine with underlying distributed grammars based on context-free rules, under = k derivation strategy. On the other hand the languages generated by some classes of cooperating distributed grammar systems may be obtained as images of regular sets through some X-machines with underlying distributed grammars. Other relations of the families of languages computed by generalised stream X-machines with the families of languages generated by cooperating distributed grammar systems are established. At the end, an example dealing with the specification of a scanner system illustrates the use of the introduced mechanism as a formal specification model.

Publisher

Association for Computing Machinery (ACM)

Subject

Theoretical Computer Science,Software

Reference13 articles.

1. Grammar systems with counting derivation and dynamical priorities

2. Cooperating distributed grammar systems: a link between formal languages and artificial intelligence;Da;Bulletin of EATCS,1991

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