Abstract
Currently we don’t have a reliable abstraction for modeling activity in knowledge-processing multiagent systems with evolving metadata. The aim of this paper is to propose an approach to simulation of evolving society of software agents with private vocabularies in form of semantic nets (also: lightweight ontologies). The conditions for successful simulation of this kind of systems are formulated with respect to up-to-day results in research on agents, Semantic Web and network theory. The generic algorithm is proposed and the importance of the presented results for predicting behavior of future autonomous agents’ societies in Web-based environments is discussed.
This work was supported by the Polish State Committee for Scientific Research under Grant No. 3 T11C 029 29 (2005-2007).
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References
Hendler, J.: Agents and the Semantic Web. IEEE Intelligent Systems 16(2), 30–37 (2001)
Hameed, A., et al.: Detecting Mismatches among Experts’ Ontologies Acquired through Knowledge Elicitation. In: Proceedings of 21th International Conference on Knowledge Based Systems and Applied Artificial Intelligence ES2001, Cambridge, UK, pp. 9–24 (2001)
Davis, M.: Semantic Wave 2006 - Part 1: Executive Guide to Billion Dollar Markets. Project10X Special Report, Washington (2006)
Berners Lee, T., Hendler, J., Lasilla, O.: The Semantic Web. Scientific American (May 2001)
Ke, J., Minett, J.W., Au, C.-P., Wang, W.S.-Y.: Self-organization and Selection in the Emergence of Vocabulary. Complexity 7(3), 41–54 (2002)
Steyvers, M., Tannenbaum, J.: The Large-Scale Structure of Semantic Networks: Statistical Analyses and a Model of Semantic Growth. Cognitive Science 29(1) (2005)
Watts, D., Strogatz, S.: Collective Dynamics of Small World Networks. Nature 393, 440–442 (1998)
Bailin, S., Truszkowski, W.: Ontology Negotiation Between Intelligent Information Agents. The Knowledge Engineering Review 17(1), 7–19 (2002)
Carrington, P., Scott, J., Wasserman, S. (eds.): Models and Methods in Social Networks Analysis. Cambridge University Press, Cambridge (2005)
Meltzoff, A.N., Prinz, W.: The imitative mind: Development, evolution, and brain bases. Cambridge University Press, Cambridge (2002)
Bales, M., Johnson, S.: Graph Theoretic Modeling of Large-Scale Semantic Networks: Methodological Review. Journal of Biomedical Informatics 39, 451–464 (2006)
Noy, N., Klein, M.: Ontology Evolution: Not the Same as Schema Evolution. Knowledge and Information Systems 6, 428–440 (2004)
Barabasi, A.-L., Albert, R.: Emergence of Scaling in Random Networks. Science 286, 509 (1999)
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Juszczyszyn, K. (2007). Modeling the Activity of a Multiagent System with Evolving Metadata. In: Nguyen, N.T., Grzech, A., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2007. Lecture Notes in Computer Science(), vol 4496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72830-6_8
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DOI: https://doi.org/10.1007/978-3-540-72830-6_8
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