On the effective distribution of knowledge represented by complementary graphs

Authors:
Leszek Kotulski;Adam Sedziwy
Affiliations:
AGH University of Sciences and Technology, Institute of Automatics, Kraków, Poland and BSW im. Tyszkiewicza, Bielsko-Biala, Poland;AGH University of Sciences and Technology, Institute of Automatics, Kraków, Poland
Venue:
KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part I
Year:
2010

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Abstract

Graph transformations are a very powerful tool for enabling formal description of the behavior of software systems. In most cases, however, they fail with regards to 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. The rules of cooperation and implicit synchronization of knowledge, in this way represented, have been already defined in [8]. Such a model is very useful in an agent environment, where subgraphs represent the individual knowledge of particular agents; this knowledge may be partially replicated and exchanged between the agents. The basic problem is 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 a 99.8% fit.