Abstract
We discuss some rough set tools for perception modelling that have been developed in our project for a system for modelling networks of classifiers for compound concepts. Such networks make it possible to recognize behavioral patterns of objects and their parts changing over time. We present a method that we call a method for on-line elimination of non-relevant parts (ENP). This method was developed for on-line elimination of complex object parts that are irrelevant for identifying a given behavioral pattern. Some results of experiments with data from the road simulator are included.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Anderson, J.R.: Rules of the mind. Lawrence Erlbaum, Hillsdale (1993)
Bar-Yam, Y.: Dynamics of Complex Systems. Addison Wesley, Reading (1997)
Bazan, J., Skowron, A.: Classifiers based on approximate reasoning schemes. In: Dunin-Keplicz, B., Jankowski, A., Skowron, A., Szczuka, M. (eds.) Monitoring, Security, and Rescue Tasks in Multiagent Systems MSRAS. Advances in Soft Computing, pp. 191–202. Springer, Heidelberg (2005)
Bazan, J., Peters, J.F., Skowron, A.: Behavioral pattern identification through rough set modelling. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W.P., Hu, X. (eds.) RSFDGrC 2005. LNCS (LNAI), vol. 3642, pp. 688–697. Springer, Heidelberg (2005) (to appear)
Bazan, J., Nguyen, S.H., Nguyen, H.S., Skowron, A.: Rough set methods in approximation of hierarchical concepts. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds.) RSCTC 2004. LNCS (LNAI), vol. 3066, pp. 346–355. Springer, Heidelberg (2004)
Kieras, D., Meyer, D.E.: An overview of the EPIC architecture for cognition and performance with application to human-computer interaction. Human-Computer Interaction 12, 391–438 (1997)
Langley, P., Laird, J.E.: Cognitive architectures: Research issues and challenges. Technical Report, Institute for the Study of Learning and Expertise, Palo Alto, CA (2002)
Laird, J.E., Newell, A., Rosenbloom, P.S.: Soar: An architecture for general intelligence. Artificial Intelligence 33, 1–64 (1987)
Luck, M., McBurney, P., Preist, C.: Agent Technology: Enabling Next Generation. A Roadmap for Agent Based Computing. Agent Link (2003)
Newell, A.: Unified Theories of Cognition. Harvard University Press, Cambridge (1990)
Nguyen, S.H., Bazan, J., Skowron, A., Nguyen, H.S.: Layered learning for concept synthesis. In: Peters, J.F., Skowron, A., Grzymała-Busse, J.W., Kostek, B.z., Świniarski, R.W., Szczuka, M.S. (eds.) Transactions on Rough Sets I. LNCS, vol. 3100, pp. 187–208. Springer, Heidelberg (2004)
Pal, S.K., Polkowski, L., Skowron, A. (eds.): Rough-Neural Computing: Techniques for Computing with Words. Cognitive Technologies. Springer, Heidelberg (2004)
Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht (1991)
Peters, J.F.: Rough ethology: Towards a biologically-inspired study of collective behavior in intelligent systems with approximation spaces. In: Peters, J.F., Skowron, A. (eds.) Transactions on Rough Sets III. LNCS(LNAI), vol. 3400, pp. 153–174. Springer, Heidelberg (2005)
The Road simulator Homepage - http://logic.mimuw.edu.pl/~bazan/simulator
The RSES Homepage – http://logic.mimuw.edu.pl/~rses
Veloso, M.M., Carbonell, J.G.: Derivational analogy in PRODIGY: Automating case acquisition, storage, and utilization. Machine Learning 10, 249–278 (1993)
Zadeh, L.A.: A new direction in AI: Toward a computational theory of perceptions. AI Magazine 22(1), 73–84 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bazan, J.G., Skowron, A. (2005). On-Line Elimination of Non-relevant Parts of Complex Objects in Behavioral Pattern Identification. In: Pal, S.K., Bandyopadhyay, S., Biswas, S. (eds) Pattern Recognition and Machine Intelligence. PReMI 2005. Lecture Notes in Computer Science, vol 3776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11590316_116
Download citation
DOI: https://doi.org/10.1007/11590316_116
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30506-4
Online ISBN: 978-3-540-32420-1
eBook Packages: Computer ScienceComputer Science (R0)