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Agents in Approximate Environments

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Games, Actions and Social Software

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7010))

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Abstract

The starting point of this research is the multimodal approach to modeling multiagent systems, especially Beliefs, Goals and Intention systems. Such an approach is suitable for specifying and verifying many subtle aspects of agents’ informational and motivational attitudes.

However, in this chapter we make a shift in a perspective. More precisely, we propose the method of embedding multimodal approaches into a form of approximate reasoning suitable for modeling perception, namely a similarity-based approximate reasoning. We argue that this formalism allows one to both keep the intuitive semantics compatible with that of multimodal logics as well as to model and implement phenomena occurring at the perception level.

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References

  1. Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley Pub. Co. (1996)

    Google Scholar 

  2. Demri, S., Orłowska, E.: Incomplete Information: Structure, Inference, Complexity. Springer, Heidelberg (2002)

    Book  MATH  Google Scholar 

  3. Doherty, P., Dunin-K\k{e}plicz, B., Szałas, A.: Dynamics of Approximate Information Fusion. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 668–677. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  4. Doherty, P., Łukaszewicz, W., Skowron, A., Szałas, A.: Knowledge Representation Techniques. A Rough Set Approach. Studies in Fuziness and Soft Computing, vol. 202. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  5. Doherty, P., Łukaszewicz, W., Szałas, A.: Similarity, Approximations and Vagueness. In: Ślęzak, D., Wang, G., Szczuka, M.S., Düntsch, I., Yao, Y. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3641, pp. 541–550. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  6. Doherty, P., Łukaszewicz, W., Szałas, A.: Tolerance Spaces and Approximative Representational Structures. In: Günter, A., Kruse, R., Neumann, B. (eds.) KI 2003. LNCS (LNAI), vol. 2821, pp. 475–489. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  7. Doherty, P., Łukaszewicz, W., Szałas, A.: Approximative query techniques for agents with heterogeneous ontologies and perceptive capabilities. In: Dubois, D., Welty, C., Williams, M.-A. (eds.) Proceedings of 9th International Conference on the Principles of Knowledge Representation and Reasoning, KR 2004, pp. 459–468. AAAI Press (2004)

    Google Scholar 

  8. Doherty, P., Łukaszewicz, W., Szałas, A.: Communication between agents with heterogeneous perceptual capabilities. Journal of Information Fusion 8(1), 56–69 (2007)

    Article  Google Scholar 

  9. Doherty, P., Magnusson, M., Szałas, A.: Approximate databases: A support tool for approximate reasoning. Journal of Applied Non-Classical Logics 16(1-2), 87–118 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  10. Doherty, P., Szałas, A.: On the Correspondence between Approximations and Similarity. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 143–152. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  11. Dunin-Kęplicz, B., Nguyen, A., Szałas, A.: Tractable approximate knowledge fusion using the Horn fragment of serial propositional dynamic logic. International Journal of Approximate Reasoning 51(3), 346–362 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  12. Dunin-Kęplicz, B., Szałas, A.: Towards Approximate BGI Systems. In: Burkhard, H.-D., Lindemann, G., Verbrugge, R., Varga, L.Z. (eds.) CEEMAS 2007. LNCS (LNAI), vol. 4696, pp. 277–287. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  13. Dunin-Kęplicz, B., Verbrugge, R.: Collective intentions. Fundamenta Informaticae 51(3), 271–295 (2002)

    MathSciNet  MATH  Google Scholar 

  14. Dunin-Kęplicz, B., Verbrugge, R.: Evolution of collective commitments during teamwork. Fundamenta Informaticae 56, 329–371 (2003)

    MathSciNet  MATH  Google Scholar 

  15. Dunin-Kęplicz, B., Verbrugge, R.: A tuning machine for cooperative problem solving. Fundamenta Informaticae 63, 283–307 (2004)

    MathSciNet  MATH  Google Scholar 

  16. Dunin-Keplicz, B., Verbrugge, R.: Teamwork in Multi-Agent Systems: A Formal Approach. John Wiley & Sons, Ltd. (2010)

    Google Scholar 

  17. Dziubiński, M., Verbrugge, R., Dunin-Kęplicz, B.: Complexity issues in multiagent logics. Fundamenta Informaticae 75(1-4), 239–262 (2007)

    MathSciNet  MATH  Google Scholar 

  18. Fagin, R., Halpern, J., Moses, Y., Vardi, M.: Reasoning about Knowledge. MIT Press, Cambridge (1995)

    MATH  Google Scholar 

  19. Fisher, M., Ladner, R.: Propositional Dynamic Logic of regular programs. Journal of Computer and System Sciences 18, 194–211 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  20. Grabowski, M., Szałas, A.: A Technique for Learning Similarities on Complex Structures with Applications to Extracting Ontologies. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds.) AWIC 2005. LNCS (LNAI), vol. 3528, pp. 183–189. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  21. Halpern, J.: Intransitivity and vagueness. In: Dubois, D., Welty, C., Williams, M.-A. (eds.) Proc. of 9th Int. Conf. KR 2004, pp. 121–129. AAAI Press (2004)

    Google Scholar 

  22. Harel, D., Kozen, D., Tiuryn, J.: Dynamic Logic. MIT Press (2000)

    Google Scholar 

  23. McCarthy, J.: Approximate objects and approximate theories. In: Cohn, A., Giunchiglia, F., Selman, B. (eds.) Proc. 7th International Conf. on Principles of Knowledge Representation and Reasoning, KR 2000, pp. 519–526. Morgan Kaufmann Pub., Inc., San Francisco (2000)

    Google Scholar 

  24. Meyer, J.-J., van der Hoek, W.: Epistemic Logic for AI and Theoretical Computer Science. Cambridge University Press, Cambridge (1995)

    Book  MATH  Google Scholar 

  25. Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)

    MATH  Google Scholar 

  26. Peleg, D.: Concurrent dynamic logic. In: STOC 1985: Proceedings of the 7th Annual ACM Symposium on Theory of Computing, pp. 232–239. ACM Press (1985)

    Google Scholar 

  27. Skowron, A., Stepaniuk, J.: Tolerance approximation spaces. Fundamenta Informaticae 27, 245–253 (1996)

    MathSciNet  MATH  Google Scholar 

  28. Słowiński, R., Vanderpooten, D.: A generalized definition of rough approximations based on similarity. IEEE Trans. on Data and Knowledge Engineering 12(2), 331–336 (2000)

    Article  Google Scholar 

  29. Williamson, T.: Vagueness. Routledge (1994)

    Google Scholar 

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Dunin-Kęplicz, B., Szałas, A. (2012). Agents in Approximate Environments. In: van Eijck, J., Verbrugge, R. (eds) Games, Actions and Social Software. Lecture Notes in Computer Science, vol 7010. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29326-9_8

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  • DOI: https://doi.org/10.1007/978-3-642-29326-9_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29325-2

  • Online ISBN: 978-3-642-29326-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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