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Simulation and Statistical Model Checking of Logic-Based Multi-Agent System Models

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 296)

Abstract

In this paper we introduce a new approach for multi-agent simulation and statistical model checking that allows the use of very generic logical models based on the well-established situation calculus to describe the behavior of agents in the context of their environment. A consequent logic-based framework is achieved by combining the situation calculus with a first order version of bounded linear time logic (BLTL) as a property specification language. This creates a much more expressive and flexible modeling-verification workflow than existing solutions.

Keywords

statistical model checking multi agent systems situation calculus discrete event simulation 

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References

  1. 1.
    Pnueli, A.: The temporal logic of programs. In: 18th Annual Symposium on Foundations of Computer Science, pp. 46–57. IEEE (1977)Google Scholar
  2. 2.
    Wald, A., et al.: Sequential tests of statistical hypotheses. Annals of Mathematical Statistics 16, 117–186 (1945)CrossRefMATHMathSciNetGoogle Scholar
  3. 3.
    Legay, A., Delahaye, B., Bensalem, S.: Statistical model checking: An overview. In: Barringer, H., et al. (eds.) RV 2010. LNCS, vol. 6418, pp. 122–135. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Younes, H.L.S., Simmons, R.G.: Probabilistic verification of discrete event systems using acceptance sampling. In: Brinksma, E., Larsen, K.G. (eds.) CAV 2002. LNCS, vol. 2404, pp. 223–235. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  5. 5.
    Aziz, A., Sanwal, K., Singhal, V., Brayton, R.: Verifying continuous time markov chains. In: Alur, R., Henzinger, T.A. (eds.) CAV 1996. LNCS, vol. 1102, pp. 269–276. Springer, Heidelberg (1996)CrossRefGoogle Scholar
  6. 6.
    Reiter, R.: Knowledge in action: logical foundations for specifying and implementing dynamical systems. MIT Press (2001)Google Scholar
  7. 7.
    De Giacomo, G., Lespérance, Y., Levesque, H.J.: Congolog, a concurrent programming language based on the situation calculus. Artificial Intelligence 121, 109–169 (2000)CrossRefMATHMathSciNetGoogle Scholar
  8. 8.
    De Giacomo, G., Lespérance, Y., Levesque, H.J., Sardina, S.: Indigolog: A high-level programming language for embedded reasoning agents. In: Multi-Agent Programming, pp. 31–72. Springer (2009)Google Scholar
  9. 9.
    Luke, S., Cioffi-Revilla, C., Panait, L., Sullivan, K., Balan, G.: Mason: A multiagent simulation environment. Simulation 81, 517–527 (2005)CrossRefGoogle Scholar
  10. 10.
    Levesque, H., Pirri, F., Reiter, R.: Foundations for the situation calculus. Linköping Electronic Articles in Computer and Information Science 3 (1998)Google Scholar
  11. 11.
    Lin, F., Reiter, R.: How to progress a database. Artificial Intelligence 92, 131–167 (1997)CrossRefMATHMathSciNetGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department for InformaticsLudwig-Maximilians-UniversitätMunichGermany

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