Expert systems for crash data collection.

Federal Highway Administration, Office of Safety and Traffic Operations, Washington, D.C.

An analysis of the distinction between deep and shallow expert systems /

This paper analyzes the relationship between the techniques used to build expert systems and the behaviors they exhibit to show that there is not sufficient evidence to link the behavioral shortcomings of first-generation expert systems to the shallow methods of representation and inference they employ. There is only evidence that the shortcomings are a consequence of a general lack of knowledge. Moreover, the paper shows that the first-generation of expert systems employ both shallow methods and most of the so-called deep methods. Lastly, we show that deeper methods augment but do not replace shallow reasoning methods; most expert systems should possess both."

Kansas nonmonetary expert system prototype /

"Contract number 99-7-4646-04-142-01."

National Traffic Data Acquisition Conference (NATDAC '94). Proceedings, volume II. Final report.

Federal Highway Administration, Washington, D.C.