closedworld

The closed-world assumption is a logical principle used in knowledge representation and databases that treats the information in a knowledge base as complete for the domain it covers. Under the closed-world assumption, statements that are not known to be true are regarded as false. This contrasts with the open-world assumption, where the absence of a fact does not imply its negation because the knowledge base may be incomplete.

In practice, the closed-world assumption is closely associated with negation as failure, a reasoning mechanism common in deductive databases and logic programming languages such as Prolog. If a query cannot be proven true from the available data, the system concludes that the negated query is true. This enables efficient, decisive inference in static, well-defined domains where all relevant facts are expected to be stored.

Applications and limitations: The closed-world assumption is appropriate when a system operates on a closed, controlled dataset where all relevant information is known. It simplifies reasoning and can improve performance for query answering. However, it risks incorrect conclusions in environments with incomplete, evolving, or partially observed data. If new facts can exist outside the current database, treating unlisted statements as false can be misleading.

Related concepts include open-world reasoning, nonmonotonic logics, and circumscription, which provide alternative approaches to handling incomplete knowledge. The choice between closed-world and open-world assumptions depends on the domain, data quality, and requirements for certainty.