Current Topics in Artificial Intelligence: 12th Conference by Daniel Borrajo, Luis Castillo, Juan Manuel Corchado

By Daniel Borrajo, Luis Castillo, Juan Manuel Corchado

This publication constitutes the refereed lawsuits of the twelfth convention of the Spanish organization for man made Intelligence, CAEPIA 2007, held in Salamanca, Spain, in November 2007, along side the seventh Workshop on man made Intelligence know-how move, TTIA 2007.

The 28 revised complete papers awarded have been rigorously chosen in the course of rounds of reviewing and development from 134 submissions. The papers tackle all present problems with synthetic intelligence starting from methodological and foundational points to complicated functions in numerous fields.

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CSLI Publications, Stanford (1996) 9. : Inducting temporal fault diagnostic rules from a qualitative model. In: Muggleton, S. ) Inductive Logic Programming, Academic Press, London (1992) 10. : Exact indexing of dynamic time warping. Knowledge and Information Systems 7(3), 358–386 (2005) 11. : An alternative approach to dependency-recording engines in consistency-based diagnosis. , Dochev, D. ) AIMSA 2000. LNCS (LNAI), vol. 1904, pp. 111–120. Springer, Heidelberg (2000) 12. : Lessons learned from diagnosing dynamic systems using possible conflicts and quantitative models.

C Springer-Verlag Berlin Heidelberg 2007 Knowledge Engineering and Planning for the Automated Synthesis 41 resources, its different learning objects and their features, and also take into account the features and needs of every student in order to elaborate, like in those strategic plans, the best learning path for every student. We must say that the use of artificial intelligence planning techniques in real applications imply a great knowledge engineering effort in order to acquire and validate the available know-how of every domain and to encode this knowledge into a set of rules or protocols which is usually named the planning domain.

4) The learning plan is translated into a form playable or understandable by the LMS. (5) The plan is executed (or played) by the student to follow the course adapted to its own features and needs. In order to guarantee a valid extraction of an HTN planning domain and a successful adaptation of the learning path, at least the following set of metadata are required to be present in the labeling of the learning objects1 : Hierarchical structure. Hierarchical relations of the form chapter/subchapter/ lesson, being lesson the atomic part of the hierarchy, are encoded by means of the is-part-of relational metadata.

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