Power properties of NLC graph grammars with a polynomial membership problem
Theoretical Computer Science
Algebraic approaches to graph transformation. Part I: basic concepts and double pushout approach
Handbook of graph grammars and computing by graph transformation
Handbook of graph grammars and computing by graph transformation
Inference of Parsable Graph Grammars for Syntactic Pattern Recognition
Fundamenta Informaticae
Distributed Graphs Transformed by Multiagent System
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
GRADIS --- Multiagent Environment Supporting Distributed Graph Transformations
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part III
Graph Multiset Transformation as a Framework for Massively Parallel Computation
ICGT '08 Proceedings of the 4th international conference on Graph Transformations
On Complexity of Coordination of Parallel Graph Transformations in GRADIS Framework
DEPCOS-RELCOMEX '09 Proceedings of the 2009 Fourth International Conference on Dependability of Computer Systems
Parallel graph transformations with double pushout grammars
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Autonomous units and their semantics - the concurrent case
Graph transformations and model-driven engineering
Parallel graph transformations supported by replicated complementary graphs
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part II
Supporting communication and cooperation in distributed representation for adaptive design
Advanced Engineering Informatics
Advanced street lighting control
Expert Systems with Applications: An International Journal
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Graph transformations are a powerful tool enabling the formal description of the behavior of software systems. In most cases, however, this tool fails due to its low efficiency. This can be overcome by introducing parallel graph transformations. The concept of complementary graphs enables two things: the decomposition of a centralized graph into many cooperating subgraphs, and their parallel transformations. Such a model is very useful in an agent environment, where subgraphs represent an individual knowledge of particular agents; this knowledge may be partially replicated and exchanged between the agents. The rules of a cooperation and an implicit synchronization of a knowledge, represented in this way, have been already defined in [10]. The second very important issue is the way of an initial graph distribution assuming the size criterion: the heuristic method proposed previously succeeds in 60% (i.e. 60% of subgraphs is consistent with the criterion). The method presented in this paper gives over 90% fit.