AI*IA 99: Advances in Artificial Intelligence: 6th Congress by Daniele Nardi, Riccardo Rosati (auth.), Evelina Lamma, Paola PDF

By Daniele Nardi, Riccardo Rosati (auth.), Evelina Lamma, Paola Mello (eds.)

ISBN-10: 3540462384

ISBN-13: 9783540462385

ISBN-10: 3540673504

ISBN-13: 9783540673507

This publication includes the prolonged types of 33 papers chosen between these initially offered on the 6th Congress of the Italian organization for man made Intelligence (AI*IA). The congress of the AI*IA is the main correct Italian occasion within the box of synthetic Intelligence, and has been receiving a lot awareness from many researchers and practitioners of alternative international locations. The 6th congress used to be held in Bologna, 14-17 September 1999, and used to be prepared in twelve clinical periods and one demo consultation. The papers right here accrued record on major paintings conducted in several parts of synthetic intelligence, in Italy and different nations. components akin to automatic reasoning, wisdom illustration, making plans, and computer studying remain completely investigated. the gathering additionally indicates a growing to be curiosity within the box of multi-agent structures, notion and robotics, and temporal reasoning. many of us contributed in numerous how one can the luck of the congress and to this quantity. to start with, the contributors of this system committee who successfully dealt with the reviewing of the sixty four papers submitted to the congress, and afterward the reviewing of the forty-one papers submitted for ebook during this quantity. They supplied 3 reports for every manuscript, by way of counting on the aid of beneficial extra reviewers. The contributors of the organizing committee, particularly Rosangela Barruffi, Paolo Bellavista, Anna Ciampolini, Marco Cremonini, Enrico Denti, Marco Gavanelli, Mauro Gaspari, Michela Milano, Rebecca Montanari, Andrea Omicini, Fabrizio Riguzzi, Cesare Stefanelli, and Paolo Torroni, labored hardy helping at fixing difficulties in the course of and after the congress.

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The subsumption hierarchy for the examples. Thick arrows denote subsumption; the thin arrows link an image to a description it satisfies. Observe that the expensive process of image retrieval can be simplified by image recognition, in the usual way a classification wrt a TBox (semantic indexing) can help query answering. In fact, given a query description D, if there exists a collection of descriptions D\,. ,, Dn to A Description Logic for Image Retrieval 21 find (most of) the images satisfying D.

The maximum (noisy-MAX) or minimum (noisy-MIN) according to this order of two given values of variables are determined. For the value highest (noisy-MAX) or lowest (noisy-MIN) in the order, Certainty-Factor-Like Structures in Bayesian Networks 33 D A B C Fig. 3. Propagation of evidence. the results are the same as for the noisy-OR and noisy-AND models. For the other values, however, the results are different from the certainty-factor model, simply because in the certainty-factor model, the uncertainties with respect to values are always produced using the same combination functions.

3. Furthermore, it is assumed that Pr(ik |w) = 0, k = 1, 2, if w ∈ {¬flu, ¬common-cold}. 6. Using the method above, the marginal probability distribution for each variable in the network has been computed, as shown in the figure. 636. 2. 4 Practical Significance Above we have seen that important Bayesian network models can be mapped to fragments of the certainty-factor model. However, the results of this paper would have little significance when in almost all practical network models the assumptions underlying decomposable, causal independence would not be satisfied.

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AI*IA 99: Advances in Artificial Intelligence: 6th Congress of Italian Association for Artificial Intelligence Bologna, Italy, September 14–17, 1999 Selected Papers by Daniele Nardi, Riccardo Rosati (auth.), Evelina Lamma, Paola Mello (eds.)


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