Abstract
In this paper we investigate a technique for fusing approximate knowledge obtained from distributed, heterogeneous information sources. We use a generalization of rough sets and relations [14], which depends on allowing arbitrary similarity relations. The starting point of this research is [2], where a framework for knowledge fusion in multi-agent systems is introduced. Agent’s individual perceptual capabilities are represented by similarity relations, further aggregated to express joint capabilities of teams. This aggregation, allowing a shift from individual to social level, has been formalized by means of dynamic logic. The approach of [2] uses the full propositional dynamic logic, not guaranteeing the tractability of reasoning. Therefore the results of [11, 12, 13] are adapted to provide a technical engine for tractable approximate database querying restricted to a Horn fragment of serial PDL. We also show that the obtained formalism is quite powerful in applications.
Supported by the MNiSW grants N N206 399134 and N N206 399334.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Demri, S.P., Orłowska, E.S.: Incomplete Information: Structure, Inference, Complexity. In: Monographs in Theoretical Computer Science. An EATCS Series. Springer, Heidelberg (2002)
Doherty, P., Dunin-Kȩplicz, 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)
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)
Doherty, P., Łukaszewicz, W., Szałas, A.: Communication between agents with heterogeneous perceptual capabilities. Journal of Information Fusion 8(1), 56–69 (2007)
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)
Dunin-Kȩplicz, 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)
Dunin-Kȩplicz, B., Verbrugge, R.: Collective intentions. Fundamenta Informaticae 51(3), 271–295 (2002)
Dunin-Kȩplicz, B., Verbrugge, R.: A tuning machine for cooperative problem solving. Fundamenta Informaticae 63, 283–307 (2004)
Harel, D., Kozen, D., Tiuryn, J.: Dynamic Logic. MIT Press, Cambridge (2000)
Maluszyński, J., Szałas, A., Vitória, A.: Paraconsistent logic programs with four-valued rough sets. In: Chan, C.-C., Grzymala-Busse, J.W., Ziarko, W.P. (eds.) RSCTC 2008. LNCS (LNAI), vol. 5306, pp. 41–51. Springer, Heidelberg (2008)
Nguyen, L.A.: On the deterministic Horn fragment of test-free PDL. In: Hodkinson, I., Venema, Y. (eds.) Advances in Modal Logic, vol. 6, pp. 373–392. King’s College Publications (2006)
Nguyen, L.A.: Weakening Horn knowledge bases in regular description logics to have PTIME data complexity. In: Ghilardi, S., Sattler, U., Sofronie-Stokkermans, V., Tiwari, A. (eds.) Proceedings of ADDCT 2007, pp. 32–47 (2007)
Nguyen, L.A.: Constructing finite least Kripke models for positive logic programs in serial regular grammar logics. Logic Journal of the IGPL 16(2), 175–193 (2008)
Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dunin-Kȩplicz, B., Nguyen, L.A., Szałas, A. (2009). Fusing Approximate Knowledge from Distributed Sources. In: Papadopoulos, G.A., Badica, C. (eds) Intelligent Distributed Computing III. Studies in Computational Intelligence, vol 237. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03214-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-03214-1_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03213-4
Online ISBN: 978-3-642-03214-1
eBook Packages: EngineeringEngineering (R0)