An MDE Approach for Modelling and Reasoning About Multi-agent Systems

  • Fazle RabbiEmail author
  • Yngve Lamo
  • Lars Michael Kristensen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10207)


Epistemic logic plays an important role in artificial intelligence for reasoning about multi-agent systems. Current approaches for modelling multi-agent systems with epistemic logic use Kripke semantics where the knowledge base of an agent is represented as atomic propositions, but intelligent agents need to be equipped with formulas to derive implicit information. In this paper, we propose a metamodelling approach where agents’ state of affairs are separated in different scopes, and the knowledge base of an agent is represented by a propositional logic language restricted to Horn clauses. We propose to use a model driven approach for the diagrammatic representation of multi-agent systems knowledge (and nested knowledge). We use a message passing for updating the state of affairs of agents and use belief revision to update the knowledge base of agents.


Model-driven engineering Epistemic logic Modal logic Knowledge base 


  1. 1.
    Barr, M., Wells, C. (eds.): Category Theory for Computing Science, 2nd edn. Prentice Hall International (UK) Ltd., Upper Saddle River (1995)zbMATHGoogle Scholar
  2. 2.
    Booth, R., Meyer, T., Varzinczak, I.J.: Next steps in propositional horn contraction. In: Boutilier, C. (ed.) Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI 2009), pp. 702–707 (2009)Google Scholar
  3. 3.
    Delgrande, J.P.: Horn clause belief change: contraction functions. In: Brewka, G., Lang, J. (eds.) Proceedings of the Eleventh International Conference on Principles of Knowledge Representation and Reasoning, KR 2008, pp. 156–165. AAAI Press (2008)Google Scholar
  4. 4.
    Diskin, Z., Wolter, U.: A diagrammatic logic for object-oriented visual modeling. Electron. Notes Theoret. Comput. Sci. 203(6), 19–41 (2008). Proceedings of the Second Workshop on Applied and Computational Category Theory (ACCAT 2007)CrossRefzbMATHGoogle Scholar
  5. 5.
    Van Ditmarsch, H., van Der Hoek, W., Kooi, B.: Dynamic Epistemic Logic, 1st edn. Springer, Heidelberg (2007)CrossRefzbMATHGoogle Scholar
  6. 6.
    Gerbrandy, J.: Dynamic epistemic logic. In: Logic, Language and Computation, Stanford, CA, USA, vol. 2, pp. 67–84. Center for the Study of Language and Information (1999)Google Scholar
  7. 7.
    Hintikka, J.: Knowledge and Belief: An Introduction to the Logic of the Two Notions. Texts in Philosophy, King’s College Publications (2005)Google Scholar
  8. 8.
    Konolige, K.: A deductive model of belief. In: Proceedings of the Eighth International Joint Conference on Artificial Intelligence - Volume 1, IJCAI 1983, San Francisco, CA, USA, pp. 377–381. Morgan Kaufmann Publishers Inc. (1983)Google Scholar
  9. 9.
    Rabbi, F., Lamo, Y., Yu, I.C.: Towards a categorical approach for meta-modelling epistemic game theory. In: Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems, MODELS 2016, pp. 57–64. ACM. New York (2016)Google Scholar
  10. 10.
    Rabbi, F., Lamo, Y., Yu, I.C., Kristensen, L.M.: WebDPF: a web-based metamodelling and model transformation environment. In: MODELSWARD 2016 - Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development, Rome, Italy, 19–21 February 2016, pp. 87–98. SciTePress (2016)Google Scholar
  11. 11.
    Rutle, A.,: Diagram predicate framework: a formal approach to MDE. Ph.D. thesis, Department of Informatics, University of Bergen, Norway (2010)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fazle Rabbi
    • 1
    • 2
    Email author
  • Yngve Lamo
    • 1
  • Lars Michael Kristensen
    • 1
  1. 1.Western Norway University of Applied SciencesBergenNorway
  2. 2.University of OsloOsloNorway

Personalised recommendations