Updating data bases with incomplete information
Suppose one wishes to construct, use, and maintain a data base of facts about the real work, even though the state of that world is only partially known. In the AI domain, this problem arises when an agent has a base set of beliefs that reflect partial knowledge about the world, and then tries to incorporate new, possibly contradictory knowledge into this set of beliefs. In the data-base domain, one facet of this situation is the well-known null values problem. The author chooses to represent such a data base as a logical theory, and views the models of the theory as representing possible states of the world that are consistent with all known information. How can new information be incorporated into the database. The research produced a formal method of specifying the desired change intensionally, by stating a well-formed formula that the state of the world is now known to satisfy. The data base update algorithms provided automatically accomplishes that change. The approach embeds the incomplete data base and the incoming information in the language of mathematical logic, and gives formal definitions of the semantics of the update operators, along with proofs of correctness for their associated algorithms. The author assesses the computational complexity of the algorithms, and proposes a means of lazy evaluation to avoid undersirable expense during execution of updates. He also examines means of enforcing integrity constraints as the data base is updated.
- Research Organization:
- Stanford Univ., CA (USA)
- OSTI ID:
- 5271703
- Resource Relation:
- Other Information: Thesis (Ph. D.)
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
ARTIFICIAL INTELLIGENCE
DATA BASE MANAGEMENT
INFORMATION VALIDATION
QUALITY CONTROL
ALGORITHMS
DATA ACQUISITION
KNOWLEDGE BASE
MATHEMATICAL LOGIC
CONTROL
MANAGEMENT
TESTING
VALIDATION
990210* - Supercomputers- (1987-1989)
990300 - Information Handling