Default reasoning about spatial occupancy
Artificial Intelligence
On the semantics of updates in databases
PODS '83 Proceedings of the 2nd ACM SIGACT-SIGMOD symposium on Principles of database systems
Combining Multiple Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Qualitative Spatial Representation and Reasoning: An Overview
Fundamenta Informaticae - Qualitative Spatial Reasoning
A Logical Formulation of Probabilistic Spatial Databases
IEEE Transactions on Knowledge and Data Engineering
A spatio-temporal logic for the specification and refinement of mobile systems
FASE'03 Proceedings of the 6th international conference on Fundamental approaches to software engineering
An AGM-style belief revision mechanism for probabilistic spatio-temporal logics
Artificial Intelligence
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There is now extensive interest in reasoning about moving objects. A PST knowledge base is a set of PST-atoms which are statements of the form "Object o is/was/will be at location L at time t with probability in the interval [L,U]". In this paper, we study mechanisms for belief revision in PST-KBs. We propose multiple methods for revising PST-KBs. These methods involve finding maximally consistent subsets, as well as changing the spatial, temporal, and probabilistic components of the atoms. We show that some methods cannot satisfy the AGM axioms for belief revision, while others do but are coNP-hard. Finally we present an algorithm for revision through probability change which runs in polynomial time and satisfies the AGM axioms.