Abstract
The multi-agent system paradigm has proven to be a useful means of abstraction when considering distributed systems with interacting components. It is often the case that each component may be viewed as an intelligent agent with specific and often limited perceptual capabilities. It is also the case that these agent components may be used as information sources and such sources may be aggregated to provide global information about particular states, situations or activities in the embedding environment. This paper investigates a framework for information fusion based on the use of generalizations of rough set theory and the use of dynamic logic as a basis for aggregating similarity relations among objects where the similarity relations represent individual agents perceptual capabilities or limitations. As an added benefit, it is shown how this idea may also be integrated into description logics.
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References
Dubois, D., Prade, H.: On the use of aggregation operations in information fusion processes. Fuzzy Sets and Systems 142, 143–161 (2004)
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)
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, Stanford, California (2004)
Doherty, P., Łukaszewicz, W., Szałas, A.: Communication between agents with heterogeneous perceptual capabilities. Journal of Information Fusion 8, 56–69 (2007)
Doherty, P., Łukaszewicz, W., Skowron, A., Szałas, A.: Knowledge Engineering Techniques. In: A Rough Set Approach, Springer, Heidelberg (2006)
Demri, S., Orłowska, E.: Incomplete Information: Structure, Inference, Complexity. Springer, Heidelberg (2002)
Harel, D., Kozen, D., Tiuryn, J.: Dynamic Logic. MIT Press, Cambridge (2000)
Rauszer, C.: Rough logic for multi-agent systems. In: Masuch, M., Polos, L. (eds.) Knowledge Representation and Reasoning Under Uncertainty. Logic at Work. LNCS (LNAI), vol. 808, pp. 161–181. Springer, Heidelberg (1994)
Nardi, D., Brachman, R.J.: An introduction to description logics. pp. 5–44 [26]
Baader, F., Nutt, W.: Basic description logics. pp. 47–100 [26]
Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)
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)
Doherty, P., Łukaszewicz, W., Szałas, A.: Approximate databases and query techniques for agents with heterogenous perceptual capabilities. In: FUSION’2004. Proceedings of the 7th Int. Conf. on Information Fusion, pp. 175–182 (2004)
Doherty, P., Łukaszewicz, W., Szałas, A.: Similarity, approximations and vagueness. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3641, Springer, Heidelberg (2005)
Komorowski, J., Pawlak, Z., Polkowski, L., Skowron, A.: Rough sets: A tutorial. pp. 3–98 [31]
Skowron, A., Stepaniuk, J.: Tolerance approximation spaces. Fundamenta Informaticae 27, 245–253 (1996)
Słowiński, R., Vanderpooten, D.: Similarity relation as a basis for rough approximations. In: Wang, P. (ed.) Advances in Machine Intelligence & Soft Computing, Raleigh NC, Bookwrights, pp. 17–33 (1997)
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)
Peleg, D.: Concurrent dynamic logic. In: STOC ’85. Proceedings of the 7th Annual ACM Symposium on Theory of Computing, pp. 232–239. ACM Press, New York (1985)
Fisher, M., Ladner, R.: Propositional Dynamic Logic of regular programs. Journal of Computer and System Sciences 18, 194–211 (1979)
Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley, Reading (1996)
Fagin, R., Halpern, J., Moses, Y., Vardi, M.: Reasoning about Knowledge. MIT Press, Cambridge (1995)
Meyer, J.J., van der Hoek, W.: Epistemic Logic for AI and Theoretical Computer Science. Cambridge University Press, Cambridge (1995)
Dunin-Kȩplicz, B., Verbrugge, R.: A tuning machine for cooperative problem solving. Fundamenta Informaticae 63, 283–307 (2004)
Dunin-Kȩplicz, B., Verbrugge, R.: Collective intentions. Fundamenta Informaticae 51(3), 271–295 (2002)
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P. (eds.): Description Logic Handbook. Cambridge University Press, Cambridge (2002)
Borgida, A., Lenzerini, M., Rosati, R.: Description logics for databases. pp. 472–494 [27]
Schild, K.: A correspondence theory for terminological logics: preliminary report. In: Proceedings of the 12th IJCAI, 466–471 (1991)
Baader, F.: Augmenting concept languages by transitive closure of roles: An alternative to terminological cycles. In: Proceedings of the 12th IJCAI, pp. 446–451 (1991)
Horrocks, I., Sattler, U.: A description logic with transitive and inverse roles and role hierarchies. Technical Report, LuFg Theoretical Computer Science, RWTH Aachen 98-05 (1998)
Pal, S., Skowron, A. (eds.): Rough Fuzzy Hybridization: A New Trend in Decision–Making. Springer, Heidelberg (1999)
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Doherty, P., Dunin-Kȩplicz, B., Szałas, A. (2007). Dynamics of Approximate Information Fusion. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_70
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DOI: https://doi.org/10.1007/978-3-540-73451-2_70
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