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  5. VOL 42, NO 5 (2020)
  6. pp. 03-23

ONTOLOGY AND MODEL OF INFORMATION TRANSFORMATION IN SITUATIONAL AGENTS’ SYSTEMS

O.E. Kovalenko

Èlektron. model. 2020, 42(5):03-23
https://doi.org/10.15407/emodel.42.05.003

ABSTRACT

A new methodological approach to information systematics is proposed. Classification features of definition of categories of information are formulated. According to this approach, a single root concept of information was introduced and its ontology was built. A model of information transformation based on the proposed ontology is developed. The application of the ontological model of information in the construction of the architecture of situational agents is presented. The universality of the proposed models is shown on the example of the BDI (beliefs, desires, intentions) agent model and the possibility of application in situational systems.

KEYWORDS

information, knowledge representation, ontology, situational management, BDI agent.

REFERENCES

  1. Singh, V.K., Gao, M. and Jain, R. (2012), “Situation recognition: an evolving problem for heterogeneous dynamic big multimedia data”, the Proceedings of the 20th ACM international conference on Multimedia, ACM, pp. 1209-1218.
    https://doi.org/10.1145/2393347.2396421
  2. Kovalenko, O.E. (2016), “Application of Ontologies in Situational Management Systems”, the Proceedings of the XV International Scientific Workshop on Modern Problems of Informatics in Management, Economics, Education, Kyiv, Svityaz, July 4-8, National Academy of Management, pp. 84-89.
  3. “Definition of information” (2018), Merriam-Webster dictionary, available at: https://www.merriam-webster.com/dictionary/information (accessed September 15, 2020)
  4. Floridi, L. (2015), “Semantic Conceptions of Information”, available at https://plato.stanford.edu/entries/information-semantic (accessed September 15, 2020)
  5. “ISO/IEC 2382-2015” (2015), Information technology, available at: https://www.iso.org/obp/ui/#iso:std:63598:en (accessed September 15, 2020)
  6. Ackoff, R.L. (1989), “From data to wisdom”, Journal of Applied Systems Analysis, Vol. 16, pp. 3-9.
  7. Adriaans, P. (2012), “Information”, The Stanford Encyclopedia of Philosophy, available at: https://plato.stanford.edu/archives/fall2013/ entries/information (accessed September 15, 2020).
  8. “Ontology Lookup Service” (2018), available at: https://www.ebi.ac.uk/ols/ search?q= information+ontology&groupField=iri&exact=on&start=0 (accessed September 15, 2020).
  9. “Information Artifact Ontology” (2017), available at: https://github.com/information-artifact-ontology/IAO (accessed September 15, 2020).
  10. “Decision cycle” (2020), available at: https://en.wikipedia.org/wiki/Decision_cycle (accessed September 15, 2020).
  11. Priemer, R. (1990), Introductory Signal Processing, World Scientific.
    https://doi.org/10.1142/0864
  12. “DSTU 2938-94” (1994), Information processing systems. Basic concepts. Terms and definitions.
  13. Kovalenko, O. (2018). “Information Taxonomy and Ontology for Situational Management”, 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies, Vol. 2, November 7, 2018, Article no. 8526723, pp. 94-97.
    https://doi.org/10.1109/STC-CSIT.2018.8526723
  14. Peirce, C. S. (1977), Semiotics and Significs, Indiana University Press, Bloomington.
  15. “ISO/IEC 11404:2007” (2007), Information technology — General-Purpose Datatypes (GPD), https://www.iso.org/standard/39479.html (accessed September 15, 2020).
  16. Panov, P., Soldatova, L.N. and Džeroski, S. (2016), "Generic ontology of datatypes", Information Sciences, Vol. 329, pp. 900-920.
    https://doi.org/10.1016/j.ins.2015.08.006
  17. “Knowledge” (2018), available at: https://en.oxforddictionaries.com/definition/knowledge (accessed September 15, 2020).
  18. “Definition of 'knowledge'” (2018), available at: https://www.collinsdictionary.com/ dictionary/english/knowledge (accessed September 15, 2020).
  19. Van, H.F., Lifschitz, V. and Porter, B. (2008), Handbook of Knowledge Representation. 
    https://doi.org/10.1016/S1574-6526(07)03003-9
  20. Rooney, D., McKenna, B. and Liesch, P. (2010), Wisdom and Management in the Knowledge Economy, Routledge, Taylor&Francis Group, NewYork, London.
  21. Ryan, S. (2014), Wisdom, The Stanford Encyclopedia of Philosophy, available at: https:// plato.stanford.edu/archives/win2014/entries/wisdom (accessed September 15, 2020).
  22. Von Neumann, J. and Morgenstern, O. (1944), Theory of games and economic behavior, Princeton University Press.
  23. Savage, L. J. (1972), The Foundations of Statistics, Dover Publications, New York.
  24. Kahneman, D. and Tversky, A. (1979), "Prospect Theory: An Analysis of Decision under Risk", Econometrica, Vol. 47, Iss. 2, pp. 263-291.
    https://doi.org/10.2307/1914185
  25. Tversky, A. and Kahneman, D. (1992), "Advances in prospect theory: Cumulative representation of uncertainty", Journal of Risk and Uncertainty, Vol. 5, Iss. 4, pp. 297-323. 
    https://doi.org/10.1007/BF00122574
  26. Kovalenko, O.Ye. (2019), “Principles of situational systems engineering”, Mathematical machines and systems, no. 4, pp. 65-78. 
    https://doi.org/10.34121/1028-9763-2019-4-65-78
  27. Nwana, H.S. (1996). "Software Agents: An Overview", The Knowledge Engineering Review, Vol. 11, Iss. 3, pp. 205-244.
    https://doi.org/10.1017/S026988890000789X
  28. Rao, A.S. and Georgeff, M.P. (1995), “BDI Agents: From Theory to Practice”, Proceedings of the First International Conference on Multiagent Systems (ICMAS), pp. 312-319.
  29. Bratman, M. (1987), “Intention, plans, and practical reason”, Harvard University Press, Vol. 10.
  30. Ravenscroft, I. (2016), Folk Psychology as a Theory, The Stanford Encyclopedia of Philosophy, available at: https://plato.stanford.edu/entries/folkpsych-theory (accessed September 15, 2020).
  31. Simon, H.A. (1955), “A Behavioral Model of Rational Choice”, Quarterly Journal of Economics, Vol. 69, Iss. 1, pp. 99-118. 
    https://doi.org/10.2307/1884852
  32. Dixon, H. (2018), Some thoughts on economic theory and artificial intelligence, Surfing Economics. Artificial Intelligence and Economic Theory, available at: https://www. huwdixon.org/SurfingEconomics/chapter7.pdf (accessed September 15, 2020).
  33. Georgeff, M.P. and Rao, A.S. (1995), “The Semantics of Intention Maintenance for Rational Agents”, IJCAI.
  34. Wooldridge, M. (2000), Reasoning about rational agents, MIT Press, Cambridge, Mass.

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