M. Laviolette and J.W. Seaman. The efficacy of fuzzy representations of uncertainty. IEEE Transactions Fuzzy Systems, 2(1):4--15, 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....uncertainty handling. Debate on the pros and cons of these two techniques for uncertainty handling has often been emotive and personalised. Advocates of probability theory and conventional statistical descriptions have criticised fuzzy theory for being un mathematical and essentially unnecessary [51, 70, 132]. Such advocates argue that probability theory can be utilised to handle any form of uncertainty in a rigorous mathematical framework, and reject the use of fuzzy theory as a sloppy convenience. Supporters of fuzzy logic argue that it encompasses probability theory, and allows for more natural ....

M. Laviolette and J.W. Seaman. The efficacy of fuzzy representations of uncertainty. IEEE Transactions Fuzzy Systems, 2(1):4--15, 1994.

....results, the known facts are whether the recognition hypothesis is correct or not. Probability is useful when dealing with serial events that require an enumeration notion of uncertainty but is not very useful when the uncertainty is about the degree of accomplishment of a known situation [5]. This is the case of confidence measuring where the task is to know for every single recognition hypothesis, its degree of possible correctness. The notion of possibility opposed to probability is a relevant contrast that fuzzy logic presents in front of probability theory. The spirit of ....

M. Laviolette and J.W. Seaman Jr. The efficacy of fuzzy representations of uncertainty. IEEE Transactions on Fuzzy Systems, 2(1):4--15, February 1994.

....aspects that approximate both theories. First, it is discussed if fuzziness is really different from the kinds of uncertainties explored by probability researchers. Second, supposing that fuzzy and probability concepts are in fact different, which theory is most adequate to represent fuzziness [Laviolette and Seaman, 1994]. Considering that the core of probability theory has been classically the study of uncertainty related to event ocurrence and fuzzy theory was developed to represent concepts, used in human reasoning and communication, which do not have a clear and precise meaning, it can be accepted that they ....

....theory and classic AI, resist to accept the new approach. A great number of discussions among fuzzy defenders and adversaries were made and continue to occur, centered basically in two aspects: i) which is the most adequate theory to handle fuzziness fuzzy or probability (see, for instance, [Laviolette and Seaman, 1994] and replies) and ii) which is the rigorous and formal definition of a fuzzy concept Indeed almost fuzzy theory (or subtheories) has been based mostly on intuitive grounds, as it was pointed out by Sheridan in a reply to [Dubois and Prade, 1988] The basic element of fuzzy theory is the notion ....

Laviolette, M. and Seaman, J., "The Efficacy of Fuzzy Representations of Uncertainty", IEEE Trans. on Fuzzy Systems, Vol. 2, No. 1, pp. 4-15, February 1994.

.... can be criticized due to its subjectivity: this is the reason why logicists argue against fuzzy logics (see a reply from Sheridan to [3] The controversy that has emerged between the fuzzy, and AI and other communities suggests that, in some extent, the fuzzy approach is not satisfactory [4][7]. The basic reason for this controversy is the lack of a formal definition of fuzzy sets, i.e. so far, a fuzzy set is a concept based on intuitive grounds. In the present paper, the concept of agreement is used to state a formal definition of fuzzy sets, allowing to raise, reframe, and solve some ....

Laviolette, M., Seaman, J.: The Efficacy of Fuzzy Representations of Uncertainty. IEEE Trans. on Fuzzy Systems, 2-1 (1994) 4-15

....theorem that guarantee that language descriptions have enough information so as to discriminate targets. This is a limiting case of the MHT paradigm that applies when dynamics of vehicles are very similar. At this time, we have no performance results comparing Bayesian and fuzzy logic approaches ([10] [11] Such comparisons typically depend critically on the test scenario and the specific definitions of Bayesian priors, conditional probabilities and fuzzy logic membership functions. Nonetheless, our implementation experience indicates that the fuzzy logic approach is more intuitive and ....

M. Laviolette, J. W. Seaman, The Efficacy of Fuzzy Representations of Uncertainty, IEEE Trans. on Fuzzy Systems, Vol. 2, No. 1, February 1994, 4-15.

....P (talljx = 180cm) denotes the likelihood that the label tall is assigned to the subject in question given that the subject s height is 180 cm. 3 Gaines (1978) also espouses a similar view in the context of the discussion Are membership functions probabilities . This debate is still alive (Laviolette J. W. Seaman 1994). Hisdal postulates that a subject s grade of membership is the modification of her (crisp) answers to the Label or Yes No experiments modified by her estimate of the error curve. These arguments essentially apply to the first type of fuzziness: errors in measurement 4 . Hisdal also goes on ....

Laviolette, M. & J. W. Seaman, J. (1994). The efficacy of fuzzy representations of uncertainty, IEEE Transactions on Fuzzy Systems 2(1): 4--15. With comments from D. Dubois and H. Prade, E. Hisdal, G. J. Klir, B. Kosko, N. Wilson, D. V. Lindley.

.... been criticized due to its subjectivity: this is the reason why logicists argue against fuzzy logics (see a reply from Sheridan to [4] The controversy that has emerged between the fuzzy, and AI and other communities suggests that, in some extent, the fuzzy approach is not yet satisfactory [6][10]. The basic reason for this controversy relies on the definition of fuzzy sets. Although there are (several) different interpretations of the partial membership concept, most of them are based on intuitive grounds, being presented a posteriori in order to justify the utilization of fuzzy sets. ....

M. Laviolette, J. Seaman, The Efficacy of Fuzzy Representations of Uncertainty, IEEE Trans. on Fuzzy Systems, 2-1:4-15, 1994.

.... by some authors to criticize the fuzzy paradigm [1] For instance, Laviolette and Seaman critisize the FST approach discussing five hypotheses that usually are assumed by FST supporters: the reality, the subjectivity, the behaviorist , the probability as fiction, and the superset hypotheses [6]. The reality hypothesis asserts that imprecision is inherent to the world, inrespective of the observer. Laviolette and Seaman defend that ambiguity of classification depends on the way human beings characterize proporties of objects and that imperfection in classfying them should rather be ....

Laviolette, M., Seaman, J.: The Efficacy of Fuzzy Representations of Uncertainty. IEEE Transactions on Fuzzy Systems, 2-1 (1994) 4-15

....get if the candidate is older than 45, then he or she is not suited for the job . But this new rule no longer has the same meaning as the first one, and the link that it establishes between age and the candidate s suitability is a travesty of the intended one. According to some pragmaticists [27], a vague term should be made clear by giving it an operational definition. Thus, the vague term young might be defined in a legal context as not older than 18 . In this way, adopting clear operational definitions can eliminate vagueness from our discourse. But this is not always possible and ....

M. Laviolette and J. W. Seaman Jr. The efficacy of fuzzy representations of uncertainty. IEEE Transactions on Fuzzy Systems, 2:4--45, 1994. with discussion.

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M. Laviolette and J.W. Seaman. The efficacy of fuzzy representations of uncertainty. IEEE Transactions Fuzzy Systems, 2(1):4--15, 1994.

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