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Extending the participatory learning paradigm to include source credibility

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Abstract

We provide an overview of the participatory learning paradigm (PLP) and discuss the importance of the acceptance function in determining which observations are used for learning. We introduce a formal model that uses this (PLP) We then extend this model in two directions. First, we consider situations in which we have incomplete observations, we only have observations about a subset of the variables of interest. Next we extend this model to allow for the inclusion in the learning process of information about the learning agents belief about the credibility of the source of the learning experience. Here we distinguish between the content of a learning experience and the source of the experience. We provide a means to allow the learning agents belief about the credibility of the source to determine the effect of the content. Furthermore we suggest a method to allow the modification of agents belief about the credibility of the source to also be part of the learning process.

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References

  • Alsina C., Trillas E., Valverde L. (1983). On some logical connectives for fuzzy set theory. Journal Mathematical of Analysis and Applications 93, 15–26

    Article  MathSciNet  MATH  Google Scholar 

  • Cryan D., Shatil S., Mayblin B. (2001). Introducing logic. Duxford, England, Totem Books

    Google Scholar 

  • Kuhn T.S. (1962). The structure of scientific revolutions. Cambridge, University of Chicago Press

    Google Scholar 

  • Quine M.V.O. (1951). Two dogmas of empiricism. Philosophical Review 60, 20–43

    Article  MATH  Google Scholar 

  • Quine M.V.O. (1953). From a logical point of view. Cambridge, Harvard Press

    MATH  Google Scholar 

  • Silva, L., Gomide, F., & Yager, R. R. (2005). Participatory learning in fuzzy clustering. In Proceedings of the 14th IEEE international conference on fuzzy systems, Reno, pp. 857–861.

  • Widrow, B., & Hoff, M. E. (1960). Adaptive switching circuits. IRE Western Electric Show and Convention Record, Part 4, pp. 96–104.

  • Yager R.R (1990). A model of participatory learning. IEEE Transactions on Systems, Man and Cybernetics 20, 1229–1234

    Article  Google Scholar 

  • Yager R.R. (2004). Participatory learning: A paradigm for building better digital and human agents. Law, Probability and Risk 3, 133–145

    Article  Google Scholar 

  • Yager R.R., Filev D.P. (1993). Modeling participatory learning as a control mechanism. International Journal of Intelligent Systems 8, 431–450

    Article  MATH  Google Scholar 

  • Yager R.R., Zhang D.Z. (1994). Effective suggestion based on participatory learning. Expert Systems: Research and Applications 7, 423–432

    Google Scholar 

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Authors and Affiliations

  1. Machine Intelligence Institute, Iona College, New Rochelle, NY, 10801, USA

    Ronald R. Yager

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  1. Ronald R. Yager
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Correspondence to Ronald R. Yager.

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Yager, R.R. Extending the participatory learning paradigm to include source credibility. Fuzzy Optim Decis Making 6, 85–97 (2007). https://doi.org/10.1007/s10700-007-9007-9

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  • DOI: https://doi.org/10.1007/s10700-007-9007-9

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