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Automatic Control and Computer Sciences

, Volume 51, Issue 7, pp 498–506 | Cite as

An Approach to Verification of a Family of Multiagent Systems for Conflict Resolution

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Abstract

In this paper, we describe a verification method for families of distributed systems generated by a context-sensitive network grammar of a special kind. The grammar includes special non-terminal symbols, so-called quasi-terminals, which uniquely correspond to grammar terminals. These quasi-terminals specify processes that are mergings of basic system processes; in contrast, simple nonterminals specify networks of parallel compositions of these processes. The verification method is based on the model-checking technique and abstraction. An abstract representative model for a family of systems depends on their specification grammar and the system properties to be verified. This model simulates the behavior of the systems in such a way that the properties holding for the representative model are satisfied for all these systems. The properties of the representative model can be verified by the model-checking method. The properties of the system generated are specified using the universal branching time logic ∀CTL with finite deterministic automata as atomic formulas. We demonstrate the application of the proposed method to verification of some properties of a multiagent system for conflict resolution, particularly for context-dependent disambiguation in ontology population. We also suggest that this approach should be used for verification of computations on subgrids that are subgraphs of computation grids. In particular, it can be used to compute the parity of the number of active processes in a subgrid.

Keywords

model checking context-sensitive network grammar multiagent systems abstractions 

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References

  1. 1.
    Bergenti, F., Franchi, E., and Poggi, A., Selected models for agent-based simulation of social networks, Proc. 3rd Symposium on Social Networks and Multiagent Systems (SNAMAS 2011), 2011, pp. 27–32.Google Scholar
  2. 2.
    Clarke, E.M., Grumberg, O., and Jha, S., Verifying parameterized networks, ACM Trans. Progr. Lang. Syst., 1997, vol. 19, no. 5, pp. 726–750.CrossRefGoogle Scholar
  3. 3.
    Clarke, E.M., Grumberg, O., and Peled, D., Model Checking, MIT Press, 1999.Google Scholar
  4. 4.
    Dassow, J., Grammars with regulated rewriting, Formal Lang. Appl. Stud. Fuzziness Soft Comp., 2004, vol. 148, pp. 249–273.MathSciNetCrossRefMATHGoogle Scholar
  5. 5.
    De Gennaro, M.C. and Jadbabaie, A., Decentralized control of connectivity for multi-agent systems, Proc. 45th IEEE Conference on Decision and Control, 2006, pp. 3628–3633.CrossRefGoogle Scholar
  6. 6.
    Fagin, R., Halpern, J.Y., Moses, Y., and Vardi, M.Y., Reasoning about Knowledge, MIT Press, 1995.MATHGoogle Scholar
  7. 7.
    Garanina, N.O. and Sidorova, E.A., Ontology population as algebraic information system processing based on multi-agent natural language text analysis algorithms, Progr. Comput. Software, 2015, vol. 41, no. 3, pp. 140–148.MathSciNetCrossRefMATHGoogle Scholar
  8. 8.
    Garanina, N. and Sidorova, E., An approach to ambiguity resolution for ontology population, Proc. 24th Int. Workshop on Concurrency, Specification, and Programming (CS&P 2015), Rzeszow, 2015, vol. 1, 2015, pp. 27–32.MATHGoogle Scholar
  9. 9.
    Garanina, N.O., Sidorova, E.A., and Anokhin, S.A., Conflict resolution in multi-agent systems with typed connections for ontology population, Perspect. Syst. Inf. Lect. Notes Comput. Sci., 2016, vol. 9609, pp. 116–129.CrossRefMATHGoogle Scholar
  10. 10.
    Hopcroft, J.E. and Ullman, J.D., Introduction to Automata Theory, Languages, and Computation, Addison-Wesley, 1979.MATHGoogle Scholar
  11. 11.
    Huhns, M.N. and Stephens, L.M., Multiagent systems and societies of agents, in Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, MIT Press, 1999, pp. 79–120.Google Scholar
  12. 12.
    Tel, G., Introduction to Distributed Algorithms, Cambridge University Press, 2000.CrossRefMATHGoogle Scholar
  13. 13.
    Wooldridge, M., An Introduction to Multiagent Systems, Willey & Sons Ltd, 2002.Google Scholar

Copyright information

© Allerton Press, Inc. 2017

Authors and Affiliations

  1. 1.Ershov Institute of Informatics Systems, Siberian BranchRussian Academy of SciencesNovosibirskRussia

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