Logic Programming Update Languages were proposed as an extension of logic programming that allows modeling the dynamics of knowledge bases where both extensional (facts) and intentional knowledge (rules) may change over time due to updates. Despite their generality, these languages do not provide a means to directly access past states of the evolving knowledge. They are limited to so-called Markovian change, i.e. changes entirely determined by the current state. We remedy this limitation by extending the Logic Programming Update Language EVOLP with LTL-like temporal operators that allow referring to the history of the evolving knowledge base, and show how this can be implemented in a Logic Programming framework.
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