Artificial Intelligence
ConGolog, a concurrent programming language based on the situation calculus
Artificial Intelligence
Two approaches to efficient open-world reasoning
Logic-based artificial intelligence
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Knowlege in action: logical foundations for specifying and implementing dynamical systems
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
Projection Using Regression and Sensors
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Theory of Relational Databases
Theory of Relational Databases
A tractability result for reasoning with incomplete first-order knowledge bases
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Artificial Intelligence
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Reiter's variant of the Situation Calculus is tightly related to relational databases, when complete information on the initial situation is available. In particular, the information on the initial situation can be seen as a relational database, and actions, as specified by the preconditions and successor state axioms, can be seen as operations that change the state of the database. In this paper, we show how to exploit such a correspondence to build systems for reasoning about actions based on standard rdational database technology. Indeed, by exploiting standlrd relational DBMS services, a system may be able to perform both Projection, exploiting DBMS querying services, and Progression, exploiting DBMS update services, in very large action theories. A key result towards such a realization, is that under very natural conditions Reiter's basic action theories turn out to be made of "safe formulas" (where basically negation is used as a form of difference between predicates only) and that regression and progression preserve such a safeness. This is a fundamental property to efficiently exploit relational database technology for reasoning. We then show that, even when action theories are not "safe", they can be made so while trying to retain efficiency as much as possible. Finally, we briefly discuss how such results can be extended to certain forms of incomplete information.