1. |
- Doherty, Patrick, 1957-, et al.
(author)
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A non-monotonic fuzzy logic.
- 1991
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In: International Fuzzy Systems Association, Fourth World Congress,1991.
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Conference paper (peer-reviewed)
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2. |
- Doherty, Patrick, 1957-, et al.
(author)
-
Fuzzy if-then-unless rules and their implementation.
- 1992
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In: International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU92,1992. - Linköping, Sweden : Springer.
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Conference paper (peer-reviewed)
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3. |
- Doherty, Patrick, 1957-, et al.
(author)
-
Fuzzy if-then-unless rules and their implementation
- 1993
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In: International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. - : World Scientific. - 0218-4885. ; 1:2, s. 167-182
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Journal article (peer-reviewed)abstract
- We consider the possibility of generalizing the notion of a fuzzy If-Then rule to take into account its context dependent nature. We interpret fuzzy rules as modeling a forward directed causal relationship between the antecedent and the conclusion, which applies in most contexts, but on occasion breaks down in exceptional contexts. The default nature of the rule is modeled by augmenting the original If-Then rule with an exception part. We then consider the proper semantic correlate to such an addition and propose a ternary relation which satisfies a number of intuitive constraints described in terms of a number of inference rules. In the rest of the paper, we consider implementational issues arising from the unless extension and propose the use of reason maintenance systems, in particular TMS's, where a fuzzy If-Then-Unless rule is encoded into a dependency net. We verify that the net satisfies the constraints stated in the inference schemes and conclude with a discussion concerning the integration of qualitative IN-OUT labelings of the TMS with quantitative degree of membership labelings for the variables in question.
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4. |
- Doherty, Patrick, 1957-, et al.
(author)
-
Nonmonotonicity, fuzziness, and multi-values.
- 1993
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In: Fuzzy Logic: State of the Art. Series D: System Theory, Knowledge Engineering and Problem Solving.. - Dordrecht ; Boston : Kluwer Academic Publishers. - 0792323246 - 9780792323242
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Book chapter (other academic/artistic)abstract
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5. |
- Doherty, Patrick, 1957-, et al.
(author)
-
Nonmonotonicity, fuzziness, and multi-values.
- 1993
-
In: Fuzzy Logic: State of the Art. Series D: System Theory, Knowledge Engineering and Problem Solving.. - Dordrecht ; Boston : Kluwer Academic Publishers. - 0792323246 - 9780792323242
-
Book chapter (other academic/artistic)abstract
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6. |
- Doherty, Patrick, 1957-, et al.
(author)
-
Partial logics and partial preferences.
- 1992
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In: International Conference on Economics/Management and Information Technology,1992. ; , s. 525-
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Conference paper (peer-reviewed)
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7. |
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8. |
- Driankov, Dimiter, 1952-, et al.
(author)
-
A non-monotonic fuzzy logic
- 1992
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In: Fuzzy Logic for the Management of Uncertainty. - New York : John Wiley & Sons. - 0471547999 ; , s. 171-190
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Book chapter (other academic/artistic)
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9. |
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10. |
- Driankov, Dimiter, 1952-, et al.
(author)
-
Fuzzy control with fuzzy inputs: the need for new rule semantics
- 1994
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In: Proceedings of the Third IEEE Conference on Fuzzy Systems, 1994. IEEE World Congress on Computational Intelligence, VOLS I-III. - : IEEE conference proceedings. - 078031896X ; , s. 111-114
-
Conference paper (peer-reviewed)abstract
- The standard computation taking place in a fuzzy logic controller proceeds from crisp inputs and via the consecutive steps of fuzzification, inference, and defuzzification computes a crisp control output. However, this computational practice simplifies to an extent the actual developments taking place in the closed loop. In reality, the knowledge about the current values of the controller input is very often available via sensory measurements. In this case, one has to take into account the negative side effects that come up with the use of sensors, in particular the presence of noisy measurements. In the paper the authors consider one particular way of dealing with noisy controller inputs, namely transforming the noise-distribution into a fuzzy set and then feeding back the so obtained fuzzy signal to the controller input. Adopting this approach requires that the shape of the input fuzzy signal should be reflected as much as possible in the output fuzzy signal so that important noise characteristics are preserved. In the paper the authors describe the requirements on the shape of the fuzzy output signal given a certain fuzzy input signal and show that the existing semantics for fuzzy IF-THEN rules do not satisfy these requirements. The authors propose new semantics for such rules which together with max-min composition produces the desired results.
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