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Intention Recognition in the Situation Calculus and Probability Theory Frameworks

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3900))

Abstract

A method to recognize agent’s intentions is presented in a framework that combines the logic of Situation Calculus and Probability Theory. The method is restricted to contexts where the agent only performs procedures in a given library of procedures, and where the system that intends to recognize the agent’s intentions has a complete knowledge of the actions performed by the agent.

An original aspect is that the procedures are defined for human agents and not for artificial agents. The consequence is that the procedures may offer the possibility to do any kind of actions between two given actions, and they also may forbid to perform some specific actions. Then, the problem is different and more complex than the standard problem of plan recognition.

To select the procedures that partially match the observations we consider the procedures that have the greatest estimated probability. This estimation is based on the application of Bayes’ theorem and on specific heuristics. These heuristics depend on the history and not just on the last observation.

A PROLOG prototype of the presented method has been implemented.

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References

  1. Albrecht, D.W., Zukerman, I., Nicholson, A.E.: Bayesian models for keyhole plan recognition in an adventure game. User modeling and user-adapted interaction 8, 5–47 (1998)

    Article  Google Scholar 

  2. Appelt, D.E., Pollack, M.E.: Weighted abduction for plan ascription. User modeling and user-adapted interaction 2, 1–25 (1991)

    Article  Google Scholar 

  3. Baier, J.A.: On procedure recognition in the Situation Calculus. In: 22nd International Conference of the Chilean Computer Science Society. IEEE Computer Society, Los Alamitos (2002)

    Google Scholar 

  4. Bauer, M.: Integrating probabilistic reasoning into plan recognition. In: Proceedings of the 11th European Conference of Artificial Intelligence. John Wiley and Sons, Chichester (1994)

    Google Scholar 

  5. Blaylock, N., Allen, J.: Corpus-based, statistical goal recognition. In: Gottlob, G., Walsh, T. (eds.) Proceedings of the 18th Inernational Joint Conference on Artificial Intelligence, pp. 1303–1308 (2003)

    Google Scholar 

  6. Boutilier, C., Reiter, R., Soutchanski, M., Thrun, S.: Decision-theoretic high-level agent programming in the situation calculus. In: Proceedings of AAAI (2000)

    Google Scholar 

  7. Carberry, S.: Incorporating default inferences into plan recognition. In: Proceedings of the 8th National Conference on Artificial Intelligence, pp. 471–478 (1990)

    Google Scholar 

  8. Charniak, E., Goldman, R.P.: A Bayesian model of plan recognition. Artificial Intelligence 64(1) (1993)

    Google Scholar 

  9. Cohen, P.R., Levesque, H.J.: Persistence, Intention, and Commitment. In: Lansky, A.L., Georgeff, M.P. (eds.) Reasoning about actions and plans, Timberline, USA, pp. 297–340 (1986)

    Google Scholar 

  10. Demolombe, R., Hamon, E.: What does it mean that an agent is performing a typical procedure? A formal definition in the Situation Calculus. In: Castelfranci, C., Lewis Johnson, W. (eds.) First International Joint Conference on Autonomous Agents and Multiagent Systems. ACM Press, New York (2002)

    Google Scholar 

  11. Otermin Fernndez, A.M.: Reconocimiento de intenciones de un operador que interacta con un sistema. Technical Report, ONERA Toulouse (2004)

    Google Scholar 

  12. Finzi, A., Lukasiewicz, T.: Game theoretic GOLOG under partial observability. In: Dignum, F., Dignum, V., Koenig, S., Kraus, S., Wooldridge, M. (eds.) Proceedings of the 4th International Conference on Autonomous Agents and Multi Agent Systems. ACM Press, New York (2005)

    Google Scholar 

  13. Kautz, H.A.: A formal theory of plan recognition and its implementation. In: Allen, J.F., Kautz, H.A., Pelavin, R.N., Tennemberg, J.D. (eds.) Reasoning about plans, pp. 69–126. Morgan Kaufmann, San Francisco (1991)

    Chapter  Google Scholar 

  14. Levesque, H., Reiter, R., Lespérance, Y., Lin, F., Scherl, R.: GOLOG: A Logic Programming Language for Dynamic Domains. Journal of Logic Programming 31, 59–84 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  15. Mao, W., Gratch, J.: A utility-based approach to intention recognition. In: Kudenko, D., Kazakov, D., Alonso, E. (eds.) AAMAS 2004. LNCS, vol. 3394. Springer, Heidelberg (2005)

    Google Scholar 

  16. Pozos Parra, P., Nayak, A., Demolombe, R.: Theories of intentions in the framework of Situation Calculus. In: Proceedings of the AAMAS workshop on Declarative Agent Languages and technologies (2004)

    Google Scholar 

  17. Reiter, R.: Knowledge in Action: Logical Foundations for Specifying and Implementing Dynamical Systems. MIT Press, Cambridge (2001)

    MATH  Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Demolombe, R., Fernandez, A.M.O. (2006). Intention Recognition in the Situation Calculus and Probability Theory Frameworks. In: Toni, F., Torroni, P. (eds) Computational Logic in Multi-Agent Systems. CLIMA 2005. Lecture Notes in Computer Science(), vol 3900. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11750734_20

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  • DOI: https://doi.org/10.1007/11750734_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33996-0

  • Online ISBN: 978-3-540-33997-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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