By Roberto Basili, Maria Teresa Pazienza
This booklet constitutes the refereed court cases of the tenth Congress of the Italian organization for synthetic Intelligence, AI*IA 2007, held in Rome, Italy, in September 2007.
The forty two revised complete papers provided including 14 revised poster papers and three invited talks have been conscientiously reviewed and chosen from eighty submissions. The papers are equipped in topical sections on wisdom illustration and reasoning, multiagent platforms, dispensed AIai, wisdom engineering, ontologies and the semantic internet, computing device studying, common language processing, details retrieval and extraction, making plans and scheduling, AI and purposes. 3 distinctive tracks depicting progresses in major software fields that signify more and more suitable issues comprise 18 extra papers on AI and robotics, AI and expressive media, and clever entry to multimedia information.
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We will show 1 In the WS literature diﬀerent ways exist to compose WSs; not all of them are based on a static model of the composition, therefore it is more general to assume that such model does not exist. 26 S. Bocconi et al. that, besides the above mentioned advantages, the usage of partial assignments allows to perform an incremental analysis that at each step takes into consideration more complex combinations of faults. Each step can reuse the results of previous ones, thereby gaining in eﬃciency.
AI*IA 2007, LNAI 4733, pp. 24–35, 2007. c Springer-Verlag Berlin Heidelberg 2007 Model-Based Diagnosability Analysis for Web Services 25 type of analysis depends on the speciﬁc formalization of the notion of diagnosis that is being used for on-line software. In this paper we analyze the problem of diagnosability, with respect to the formalization of diagnosis introduced in  and the algorithm described in . Before giving a short description of this framework, it is worth pointing out some peculiarities of the WS scenario, that pose some interesting problems with respect to existing literature on diagnosability analysis.
This is straightforward for discriminability: Property 3. Let pfm1 and pfm2 be two discriminable partial fault modes. Then each pfm1 , reﬁnement of pfm1 , and pfm2 , reﬁnement of pfm2 , are discriminable. Indiscriminability can be inferred under appropriate conditions: Property 4. Let pfm1 and pfm2 be two alternative not discriminable partial fault modes. Let D denote their (coincident) domain and Ext(pfm1 ), Ext(pfm2 ) their complete sets of admissible extensions. Let m be a mode variable with Dom(m) ∩ D = ∅.