An action language based on causal explanation: preliminary report
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
LPSS '92 Proceedings of the Second International Logic Programming Summer School on Logic Programming in Action
Default Negated Conclusions: Why Not?
ELP '96 Proceedings of the 5th International Workshop on Extensions of Logic Programming
Embracing causality in specifying the indirect effects of actions
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
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This paper has two main objectives. One is to show that the dynamic knowledge representation paradigm introduced in [ALP+00] and the associated language LUPS, defined in [APPP99], constitute natural, powerful and expressive tools for representing dynamically changing knowledge. We do so by demonstrating the applicability of the dynamic knowledge representation paradigm and the language LUPS to several broad knowledge representation domains, for each of which we provide an illustrative example. Our second objective is to extend our approach to allow proper handling of conflicting updates. So far, our research on knowledge updates was restricted to a two-valued semantics, which, in the presence of conflicting updates, leads to an inconsistent update, even though the updated knowledge base does not necessarily contain any truly contradictory information. By extending our approach to the three-valued semantics we gain the added expressiveness allowing us to express undefined or noncommittal updates.