Introduction to graph theory
Artificial Intelligence
Preferential Semantics for Causal Fixpoints
AI '97 Proceedings of the 10th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
A causal theory of ramifications and qualifications
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Causal Propagation Semantics - A Study
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
A unifying semantics for causal ramifications
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
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In the present work we examine the causal theory of actions put forward by McCain and Turner [McCain and Turner, 1995] for determining ramifications. Our principal aim is to provide a characterisation of this causal theory of actions in terms of a Shoham-like preferential semantics [Shoham, 1988]. This would have a twofold advantage: it would place McCain and Turner's theory in perspective, allowing a comparison with other logics of action; and, it would allow us to glean further insights into the nature of causality underlying their work. We begin by showing that our aim is not attainable by a preferential mechanism alone. At this point we do not abandon preferential semantics altogether but augment it in order to arrive at the desired result. We draw the following moral which is at the heart of our paper: two components -- minimal change under a preferential structure and causality -- are required to provide a concise solution to the frame and ramification problems.