Previous |  Up |  Next

Article

Title: From ignorance to uncertainty: a conceptual analysis (English)
Author: Baroni, Pietro
Author: Guida, Giovanni
Author: Mussi, Silvano
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 34
Issue: 1
Year: 1998
Pages: [105]-120
Summary lang: English
.
Category: math
.
Summary: 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. (English)
Keyword: uncertainty
Keyword: relational knowledge
MSC: 68T37
idZBL: Zbl 1274.68513
.
Date available: 2009-09-24T19:14:09Z
Last updated: 2015-03-27
Stable URL: http://hdl.handle.net/10338.dmlcz/135189
.
Reference: [1] Bacchus F.: Representing and Reasoning with Probabilistic Knowledge.A Logical Approach to Probabilities. MIT Press, Cambridge 1990 MR 1133623
Reference: [2] Baroni P., Guida G., Mussi S.: Modeling default reasoning through $A$–uncertainty.In: Proceedings IPMU’ 96, International Conference on Information Processing and Management of Uncertainty in Knowledge–Based Systems, Granada 1996, pp. 1197–1204
Reference: [3] Benferhat S., Saffiotti A., Smets P.: Belief functions and default reasoning.In: Proc. UAI 95 11th Conference on Uncertainty in Artificial Intelligence, Montreal 1995 Zbl 0948.68112, MR 1785699
Reference: [4] Dubois D., Lang J., Prade H.: Automated reasoning using possibilistic logic: Semantics, belief revision, and variable certainty weights.IEEE Trans. Knowledge Data Engineering KDE–6 (1994), 1, 64–71 MR 1281429, 10.1109/69.273026
Reference: [5] Halpern J. Y.: An analysis of first–order logics of probability.Artificial Intelligence 46 (1990), 311–350 Zbl 0723.03007, MR 1084887, 10.1016/0004-3702(90)90019-V
Reference: [6] Group, Léa Sombé: Reasoning under incomplete information in artificial intelligence: A comparison of formalisms using a single example.Internat. J. Intelligent Systems 5 (1990), 4, 323–472 MR 1094371, 10.1002/int.4550050403
Reference: [7] Moses Y., Shoham Y.: Belief as defeasible knowledge.Artificial Intelligence 64 (1993), 299–321 Zbl 0787.68095, MR 1259580, 10.1016/0004-3702(93)90107-M
Reference: [8] Nilsson N. J.: Probabilistic logic.Artificial Intelligence 28 (1986), 71–87 Zbl 0589.03007, MR 0832294, 10.1016/0004-3702(86)90031-7
Reference: [9] Pearl J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference.Morgan Kaufmann, San Mateo 1991 Zbl 0746.68089, MR 0965765
Reference: [10] Reiter R.: Nonmonotonic reasoning.Ann. Rev. Computer Science 2 (1987), 147–186 MR 0921495, 10.1146/annurev.cs.02.060187.001051
Reference: [11] 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
Reference: [12] Saffiotti A.: A belief–function logic In: Proc.AAAI–92 10th National Conference on Artificial Intelligence, San Jose, 1992, pp. 642–647 MR 1203139
Reference: [13] Smets P.: The nature of unnormalized beliefs encountered in the transferable belief model.In: Proc. of Uncertainty in AI 92, pp. 292–297
Reference: [14] 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
.

Files

Files Size Format View
Kybernetika_34-1998-1_10.pdf 2.142Mb application/pdf View/Open
Back to standard record
Partner of
EuDML logo