Programmed Graph Replacement Systems

Schürr, Andreas

doi:10.1142/9789812384720_0007

Cited by 55 publications

(30 citation statements)

References 21 publications

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“…the use of graph schemata in PROGRES [17]). Another form of typing in the area of graph transformation can be found in the notion of pair grammars and triple grammars where a pair resp.…”

Section: G(x)mentioning

confidence: 99%

“…If G =⇒ r H, one says that G directly derives H by applying r. There are many possibilities to choose rules and their applications. Types of rules may vary from the more restrictive ones, like edge replacement [4] or node replacement [8], to the more general ones, like double-pushout rules [2], single-pushout rules [6], or PROGRES rules [17].…”

Section: Rule Basesmentioning

confidence: 99%

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Typing of Graph Transformation Units

Klempien-Hinrichs

Kreowski

Kuske

2004

Lecture Notes in Computer Science

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Abstract. The concept of graph transformation units in its original sense is a structuring principle for graph transformation systems which allows the interleaving of rule applications with calls of imported units in a controlled way. The semantics of a graph transformation unit is a binary relation on an underlying type of graphs. In order to get a flexible typing mechanism for transformation units and a high degree of parallelism this paper introduces typed graph transformation units that transform k-tuples of typed input graphs into l-tuples of typed output graphs in a controlled and structured way. The transformation of the typed graph tuples is performed with actions that apply graph transformation rules and imported typed units simultaneously to the graphs of a tuple. The transformation process is controlled with control conditions and with graph tuple class expressions. The new concept of typed graph transformation units is illustrated with examples from the area of string parsing with finite automata.

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“…the use of graph schemata in PROGRES [17]). Another form of typing in the area of graph transformation can be found in the notion of pair grammars and triple grammars where a pair resp.…”

Section: G(x)mentioning

confidence: 99%

Section: Rule Basesmentioning

confidence: 99%

Typing of Graph Transformation Units

Klempien-Hinrichs

Kreowski

Kuske

2004

Lecture Notes in Computer Science

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“…Rule classes may vary from the more restrictive ones, like edge replacement (Drewes & Kreowski & Habel, 1997) or node replacement (Engelfriet, & Rozenberg, 1997), to the more general ones, like doublepushout rules , single-pushout rules , or PROGRES rules (Schürr, 1997). In this paper, we use rules of the form r = (L → K R) where L and R are graphs (the left-and right-hand side of r, respectively) and K is a set of nodes shared by L and R. In a graphical representation of r, L and R are drawn as usual, with numbers uniquely identifying the nodes in K. Its application means to replace an occurrence of L with R such that the common part K is kept.…”

Section: Graph Transformationmentioning

confidence: 99%

Rule-Based Transformation of Graphs and the Product Type

Klempien-Hinrichs¹,

Kreowski²,

Kuske³

Transformation of Knowledge, Information and Data

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“…The burden of proving the rule correct lies upon the user or an automated rule defining procedure. These kind of rules are the ones typically used in graph rewriting systems (Schürr, 1997).…”

Section: Plan-rewriting Rules: Full Versus Partial Specificationmentioning

confidence: 99%

“…PbR builds on ideas from graph rewriting (Schürr, 1997). The plan-rewriting rules in PbR are an extension of traditional graph rewriting rules.…”

Section: Related Workmentioning

confidence: 99%

Plan Optimization by Plan Rewriting

Ambite¹,

Knoblock²,

Minton³

Intelligent Techniques for Planning

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Planning by Rewriting (PbR) is a paradigm for efficient high-quality planning that exploits declarative plan rewriting rules and efficient local search techniques to transform an easy-to-generate, but possibly suboptimal, initial plan into a high-quality plan. In addition to addressing planning efficiency and plan quality, PbR offers a new anytime planning algorithm. The plan rewriting rules can be either specified by a domain expert or automatically learned. We describe a learning approach based on comparing initial and optimal plans that produces rules competitive with manually-specified ones. PbR is fully implemented and has been applied to several existing domains. The experimental results show that the PbR approach provides significant savings in planning effort while generating high-quality plans.

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Programmed Graph Replacement Systems

Cited by 55 publications

References 21 publications

Typing of Graph Transformation Units

Typing of Graph Transformation Units

Rule-Based Transformation of Graphs and the Product Type

Plan Optimization by Plan Rewriting

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