Abstract
Update of knowledge bases is becoming an important topic in Artificial Intelligence and a key problem in knowledge representation and reasoning. One of the latest ideas to update logic programs is choosing between models of Minimal Generalised Answer Sets to overcome disadvantages of previous approaches. This paper describes an implementation of the declarative version of updates sequences that has been proposed as an alternative to syntax-based semantics. One of the main contributions of this implementation is to use DLV’s Weak Constraints to compute the model(s) of an update sequence, besides presenting the precise definitions proposed by the authors and an online solver. As a result, the paper makes an outline of the basic structure of the system, describes the employed technology, discusses the major process of computing the models, and illustrates the system through examples.
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Acosta Guadarrama, J.C. (2007). Implementing Knowledge Update Sequences. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_25
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DOI: https://doi.org/10.1007/978-3-540-76631-5_25
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