From ignorance to uncertainty: a conceptual analysis
Pietro Baroni; Giovanni Guida; Silvano Mussi
Kybernetika (1998)
- Volume: 34, Issue: 1, page [105]-120
- ISSN: 0023-5954
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topBaroni, Pietro, Guida, Giovanni, and Mussi, Silvano. "From ignorance to uncertainty: a conceptual analysis." Kybernetika 34.1 (1998): [105]-120. <http://eudml.org/doc/33338>.
@article{Baroni1998,
abstract = {This paper aims to develop an analysis of how ignorance affects the reasoning activity and is related to the concept of uncertainty. With reference to a simple inferential reasoning step, involving a single piece of relational knowledge, we identify four types of ignorance and show how they give rise to different types of uncertainty. We then introduce the concept of reasoning attitude, as a basic choice about how reasoning should be carried out in presence of ignorance. We identify two general attitudes, analyze how they are related to different types of ignorance, and propose some general requirements about how they should affect the reasoning activity. A formalism for uncertain reasoning explicitly including the different types of uncertainty identified and satisfying the stated requirements is finally introduced and its performance is analyzed in simple examples.},
author = {Baroni, Pietro, Guida, Giovanni, Mussi, Silvano},
journal = {Kybernetika},
keywords = {uncertainty; relational knowledge; uncertainty; relational knowledge},
language = {eng},
number = {1},
pages = {[105]-120},
publisher = {Institute of Information Theory and Automation AS CR},
title = {From ignorance to uncertainty: a conceptual analysis},
url = {http://eudml.org/doc/33338},
volume = {34},
year = {1998},
}
TY - JOUR
AU - Baroni, Pietro
AU - Guida, Giovanni
AU - Mussi, Silvano
TI - From ignorance to uncertainty: a conceptual analysis
JO - Kybernetika
PY - 1998
PB - Institute of Information Theory and Automation AS CR
VL - 34
IS - 1
SP - [105]
EP - 120
AB - This paper aims to develop an analysis of how ignorance affects the reasoning activity and is related to the concept of uncertainty. With reference to a simple inferential reasoning step, involving a single piece of relational knowledge, we identify four types of ignorance and show how they give rise to different types of uncertainty. We then introduce the concept of reasoning attitude, as a basic choice about how reasoning should be carried out in presence of ignorance. We identify two general attitudes, analyze how they are related to different types of ignorance, and propose some general requirements about how they should affect the reasoning activity. A formalism for uncertain reasoning explicitly including the different types of uncertainty identified and satisfying the stated requirements is finally introduced and its performance is analyzed in simple examples.
LA - eng
KW - uncertainty; relational knowledge; uncertainty; relational knowledge
UR - http://eudml.org/doc/33338
ER -
References
top- Bacchus F., Representing and Reasoning with Probabilistic Knowledge, A Logical Approach to Probabilities. MIT Press, Cambridge 1990 MR1133623
- Baroni P., Guida G., Mussi S., Modeling default reasoning through –uncertainty, In: Proceedings IPMU’ 96, International Conference on Information Processing and Management of Uncertainty in Knowledge–Based Systems, Granada 1996, pp. 1197–1204 (1996)
- Benferhat S., Saffiotti A., Smets P., Belief functions and default reasoning, In: Proc. UAI 95 11th Conference on Uncertainty in Artificial Intelligence, Montreal 1995 Zbl0948.68112MR1785699
- Dubois D., Lang J., Prade H., 10.1109/69.273026, IEEE Trans. Knowledge Data Engineering KDE–6 (1994), 1, 64–71 (1994) MR1281429DOI10.1109/69.273026
- Halpern J. Y., 10.1016/0004-3702(90)90019-V, Artificial Intelligence 46 (1990), 311–350 (1990) Zbl0723.03007MR1084887DOI10.1016/0004-3702(90)90019-V
- Group, Léa Sombé, 10.1002/int.4550050403, Internat. J. Intelligent Systems 5 (1990), 4, 323–472 (1990) MR1094371DOI10.1002/int.4550050403
- Moses Y., Shoham Y., 10.1016/0004-3702(93)90107-M, Artificial Intelligence 64 (1993), 299–321 (1993) Zbl0787.68095MR1259580DOI10.1016/0004-3702(93)90107-M
- Nilsson N. J., 10.1016/0004-3702(86)90031-7, Artificial Intelligence 28 (1986), 71–87 (1986) Zbl0589.03007MR0832294DOI10.1016/0004-3702(86)90031-7
- Pearl J., Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference, Morgan Kaufmann, San Mateo 1991 Zbl0746.68089MR0965765
- Reiter R., 10.1146/annurev.cs.02.060187.001051, Ann. Rev. Computer Science 2 (1987), 147–186 (1987) MR0921495DOI10.1146/annurev.cs.02.060187.001051
- Saffiotti A., Using Dempster–Shafer theory in knowledge representation, In: Uncertainty in Artificial Intelligence 6 (P. P. Bonissone, M. Henrion, L. N. Kanal and J. F. Lemmer, eds.), Elsevier, New York 1991, pp. 417–431 (1991)
- Saffiotti A., A belief–function logic In: Proc, AAAI–92 10th National Conference on Artificial Intelligence, San Jose, 1992, pp. 642–647 (1992) MR1203139
- Smets P., The nature of unnormalized beliefs encountered in the transferable belief model, In: Proc. of Uncertainty in AI 92, pp. 292–297
- Smets P., Hsia Y. T., Default reasoning and the transferable belief model, In: Uncertainty in Artificial Intelligence 6 (P. P. Bonissone, M. Henrion, L. N. Kanal and J. F. Lemmer, eds.). Elsevier, New York 1991, pp. 495–504 (1991)
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