Knowledge Acquisition Evaluation Using Simulated Experts

Cao, Tri M.; Compton, Paul

doi:10.1007/11891451_6

Cited by 3 publications

(1 citation statement)

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“…Later and more relevant research to our work here, is concerned with analyzing the knowledge acquisition process itself or formalizing the resultant knowledge in order to assess its representational capacity, e.g. [14,24]. Our work extends this second category of research to map not only the RDR knowledge base to default logic rules, but also the incremental process of generating RDR to one of generating default logic statements.…”

Section: Related Work and Backgroundmentioning

confidence: 98%

Constructing enhanced default theories incrementally

Beydoun

Hoffmann

Gill

2017

Complex Intell. Syst.

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The main difference between various formalisms of non-monotonic reasoning is the representation of nonmonotonic rules. In default logic, they are represented by special expressions called defaults. In default logic, commonsense knowledge about the world is represented as a set of named defaults. The use of defaults is popular because they reduce the complexity of the representation, and they are sufficient for knowledge representation in many naturally occurring contexts. This paper offers an incremental process to acquire defaults from human experts directly and at the same time it provides added semantics to defaults by adding priorities to defaults and creating additional relations between them. The paper uses an existing incremental framework, NRDR, to generate these defaults. This framework is chosen as it not only enables incremental context driven formulation of defaults, but also allows experts to introduce their own domain terms. In choosing this framework, the paper broadens its utility.

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Section: Related Work and Backgroundmentioning

confidence: 98%