Abstract
Logic Programming Update Languages have been proposed as extensions of logic programming that allow specifying and reasoning about knowledge bases where both extensional knowledge (facts) as well as intentional knowledge (rules) may change over time as a result of updates.
Despite their generality, these languages are limited in that they do not provide a means to directly access past states of the evolving knowledge. They only allow for so-called Markovian change, i.e. change which is entirely determined by the current state of the knowledge base.
After motivating the need for non-Markovian change, we extend the language EVOLP – a Logic Programming Update Language – with Linear Temporal Logic-like operators, which allow referring to the history of an evolving knowledge base. We then show that it is in fact possible to embed the extended EVOLP into the original one, thus demonstrating that EVOLP itself is expressive enough to encode non-Markovian dynamic knowledge bases. This embedding additionally sheds light on the relationship between Logic Programming Update Languages and Modal Temporal Logics. The embedding is also the starting point of our implementation.
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Alferes, J.J., Gabaldon, A., Leite, J. (2011). Evolving Logic Programs with Temporal Operators. In: Balduccini, M., Son, T.C. (eds) Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning. Lecture Notes in Computer Science(), vol 6565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20832-4_14
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DOI: https://doi.org/10.1007/978-3-642-20832-4_14
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