Title :
Learning from historical precedent
Author :
Pazzani, Michael J.
Author_Institution :
Dept. of Inf. & Comput. Sci., California Univ., Irvine, CA, USA
Abstract :
Explanation-based learning, a method of abstracting general principles from a small number of prior cases, is discussed. The author demonstrates the feasibility of applying this method to economic sanction incidents. This approach is contrasted with regression analysis, a traditional quantitative method. A method for integrating these two approaches is proposed
Keywords :
economics; expert systems; explanation; government data processing; learning systems; economic sanction incidents; explanation based learning; historical precedent; regression analysis; Africa; Australia; Computer science; Decision making; Economic forecasting; Failure analysis; History; Learning systems; Regression analysis; Testing;
Conference_Titel :
AI Systems in Government Conference, 1989.,Proceedings of the Annual
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-1934-1
DOI :
10.1109/AISIG.1989.47318
