Consistency and Plausible Inference,
Abstract
Research in expert systems is concerned with how to represent and reproduce the problem-solving skills that experts exhibit in their respective domains. One of the most basic of these skills is the ability to put two together--to draw reasoned conclusions that supplement direct observations. This poses a difficulty because our models of reasoning are derived from the deduction mechanisms of logic and, almost without exception, investigators have noted that expert reasoning beyond a superficial level cannot be understood in terms of such precise schema. Logic deals with an idealized world in which facts are known with certainty and rules of inference allow other facts to be deduced with equal certainty. Experts, on the other hand, are usually required to form judgments based on evidence. Such evidence may be required to form judgments based on evidence. Such evidence may be subject to uncertainties arising from errors of measurment or difficulty of interpretation. The study of how to overcome difficulties such as inconsistency and lack of definitiveness and still reach reasonable, supportable conclusions is called plausible or uncertain inference.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 1982
- Accession Number
- ADA136186
Entities
People
- J. R. Quinlan
Organizations
- RAND Corporation