Hybrid Knowledge Bases

• Authors: James J. Lu;Anil Nerode;V. s. Subrahmanian
• Venue: IEEE Transactions on Knowledge and Data Engineering
• Year: 1996

Deductive databases that interact with, and are accessed by, reasoning agents in the real world (such as logic controllers in automated manufacturing, weapons guidance systems, aircraft landing systems, land-vehicle maneuvering systems, and air-traffic control systems) must have the ability to deal with multiple modes of reasoning. Specifically, the types of reasoning we are concerned with include, among others, reasoning about time, reasoning about quantitative relationships that may be expressed in the form of differential equations or optimization problems, and reasoning about numeric modes of uncertainty about the domain which the database seeks to describe. Such databases may need to handle diverse forms of data structures, and frequently they may require use of the assumption-based nonmonotonic representation of knowledge.A hybrid knowledge base is a theoretical framework capturing all the above modes of reasoning. The theory tightly unifies the Constraint Logic Programming Scheme of Jaffar and Lassez [12], the Generalized Annotated Logic Programming Theory of Kifer and Subrahmanian [17], and the Stable Model semantics of Gelfond and Lifschitz [7]. New techniques are introduced which extend both the work on Annotated Logic Programming and the Stable Model semantics. (Proofs are omitted from the paper to ensure readability. Complete details of all results may be found in [24].)