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Computational Complexity of Planning and Approximate Planning in Presence of Incompleteness.

, , and . IJCAI, page 948-955. Morgan Kaufmann, (1999)

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In Engineering Classes, How to Assign Partial Credit: From Current Subjective Practice to Exact Formulas (Based on Computational Intelligence Ideas)., , and . SSCI, page 1621-1626. IEEE, (2015)Towards Efficient Prediction of Decisions under Interval Uncertainty., , , and . PPAM, volume 4967 of Lecture Notes in Computer Science, page 1372-1381. Springer, (2007)From Gauging Accuracy of Quantity Estimates to Gauging Accuracy and Resolution of Measuring Physical Fields., and . PPAM (2), volume 6068 of Lecture Notes in Computer Science, page 456-465. Springer, (2009)From 1-D to 2-D fuzzy: A proof that interval-valued and complex-valued are the only distributive options., , and . NAFIPS/WConSC, page 1-6. IEEE, (2015)Sometimes, it is beneficial to process different types of uncertainty separately., , and . NAFIPS/WConSC, page 1-5. IEEE, (2015)50 Years of Fuzzy Sets: Preface., and . International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, (2015)Optimal choice of granularity in commonsense estimation: Why half-orders of magnitude?, and . Int. J. Intell. Syst., 21 (8): 843-855 (2006)Guest Editors' Introduction: Interval Methods in Representing and Processing Uncertainty.. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 5 (3): 221-222 (1997)Interval Methods in Knowledge Representation.. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 5 (6): 733-734 (1997)Corrigendum: Interval Methods In Knowledge Representation (Abstracts Of Recent Papers).. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 12 (1): 127 (2004)