Measuring instability in normal residuated logic programs: Adding information

 

Abstract

Inconsistency in the framework of general resid-uated logic programs can be, somehow, decomposed into two notions: incoherence and instability. In this work, we focus on the measure of instability of normal residuated programs. Some measures were already provided and initial results obtained in terms of the amount of information that have to be discarded in order to recover stability; in this paper, our interest is focused precisely on the case in which stability can be recovered by adding information to our program.

Citation

Please, cite this work as:

[MO10] N. Madrid and M. Ojeda-Aciego. “Measuring instability in normal residuated logic programs: Adding information”. In: FUZZ-IEEE 2010, IEEE International Conference on Fuzzy Systems, Barcelona, Spain, 18-23 July, 2010, Proceedings. IEEE, 2010, pp. 1-7. DOI: 10.1109/FUZZY.2010.5584819. URL: https://doi.org/10.1109/FUZZY.2010.5584819.

BibTeX

@InProceedings{Madrid2010,
     author = {Nicol{’a}s Madrid and Manuel Ojeda-Aciego},
     booktitle = {{FUZZ-IEEE} 2010, {IEEE} International Conference on Fuzzy Systems, Barcelona, Spain, 18-23 July, 2010, Proceedings},
     title = {Measuring instability in normal residuated logic programs: Adding information},
     year = {2010},
     pages = {1–7},
     publisher = {{IEEE}},
     bibsource = {dblp computer science bibliography, https://dblp.org},
     biburl = {https://dblp.org/rec/conf/fuzzIEEE/MadridO10.bib},
     doi = {10.1109/FUZZY.2010.5584819},
     timestamp = {Mon, 03 Jan 2022 00:00:00 +0100},
     url = {https://doi.org/10.1109/FUZZY.2010.5584819},
}

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Measuring instability in normal residuated logic programs: Adding information

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Papers citing this work

The following is a non-exhaustive list of papers that cite this work:

[1] M. E. Cornejo, D. Lobo, and J. Medina. “Measuring the Incoherent Information in Multi-adjoint Normal Logic Programs”. In: Advances in Fuzzy Logic and Technology 2017. Springer International Publishing, Sep. 2017, p. 521–533. ISBN: 9783319668307. DOI: 10.1007/978-3-319-66830-7_47. URL: http://dx.doi.org/10.1007/978-3-319-66830-7_47.

[2] M. E. Cornejo, D. Lobo, and J. Medina. “Selecting the Coherence Notion in Multi-adjoint Normal Logic Programming”. In: Advances in Computational Intelligence. Springer International Publishing, 2017, p. 447–457. ISBN: 9783319591537. DOI: 10.1007/978-3-319-59153-7_39. URL: http://dx.doi.org/10.1007/978-3-319-59153-7_39.

[3] J. Janssen, S. Schockaert, D. Vermeir, et al. “A core language for fuzzy answer set programming”. In: International Journal of Approximate Reasoning 53.4 (Jun. 2012), p. 660–692. ISSN: 0888-613X. DOI: 10.1016/j.ijar.2012.01.005. URL: http://dx.doi.org/10.1016/j.ijar.2012.01.005.

[4] J. Janssen, S. Schockaert, D. Vermeir, et al. “Aggregated Fuzzy Answer Set Programming”. In: Annals of Mathematics and Artificial Intelligence 63.2 (Aug. 2011), p. 103–147. ISSN: 1573-7470. DOI: 10.1007/s10472-011-9256-8. URL: http://dx.doi.org/10.1007/s10472-011-9256-8.

[5] N. Madrid and M. Ojeda-Aciego. “Measuring Inconsistency in Fuzzy Answer Set Semantics”. In: IEEE Transactions on Fuzzy Systems 19.4 (Aug. 2011), p. 605–622. ISSN: 1941-0034. DOI: 10.1109/tfuzz.2011.2114669. URL: http://dx.doi.org/10.1109/tfuzz.2011.2114669.

[6] N. Madrid and M. Ojeda-Aciego. “On the use of fuzzy stable models for inconsistent classical logic programs”. In: 2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI). IEEE, Apr. 2011, p. 115–121. DOI: 10.1109/foci.2011.5949476. URL: http://dx.doi.org/10.1109/foci.2011.5949476.