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University of Aberdeen (1996) 17. : Physical negation: Introducing fault models into the general diagnostic engine. In: Eleventh International Joint Conference on Artificial Intelligence (IJCAI 1989), Detroit, Michigan, USA (1989) 18. : Diagnosis progresiva en el tiempo de sistemas dinámicos. In: IV Jornadas de ARCA, Sistemas Cualitativos y Diagnosis, JARCA’02 (2002) 19. : A neural network methodology for process fault diagnosis. AIChE J. 35(12), 1993–2001 (1989) 20. : Stacked generalization. es Abstract.

This particular interaction describes the interoperation of Bayesian evidence from the Learner Agent to the Social Agent. 33, in the node Credibility. The reception of this evidence by the Social Agent will trigger the Bayesian inference process, generating a new situation in the Bayesian network illustrated in the Figure 2. 33 Fig. 3. Interoperability among Social Agent and Learner Agent 4 Conclusions In this paper, we present a cognitive agent model capable of deals with social and affective skills of students in order to improve collaboration.

The method consists of identifying interesting word co-occurrences from the texts, and then of retrieving relevant concepts for each co-occurrence using an extension of a word sense disambiguation algorithm. There exists many applications for a concept retrieval system. The most direct one is the semantic annotation of texts with respect to an existing knowledge resource like WordNet, UMLS1 in Medicine or Wikipedia. gov/ D. Borrajo, L. M. ): CAEPIA 2007, LNAI 4788, pp. 21–30, 2007. c Springer-Verlag Berlin Heidelberg 2007 22 H.

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