The ALFALFA entomology pest identification system
Rule groups with preconditions, postconditions, and termination conditions were added to the ADVISE Meta-Expert System. Multiple, varying goals are also an attribute of the new rule groups. By treating the data collection process as separating from the rule inference engine, techniques for enhanced data acquisition were developed using semantic networks to describe relations among variables and to restructure value sets for variables dynamically. Having thus extended the ADVISE tools, an automated key to alfalfa field pest identification was selected as a test application and found to be particularly well suited by the new features. A need for disjunctive (“OR”) constructs in the right hand side of rules is discussed, and directions for future applications are given.
KeywordsExpert System Semantic Network Rule Group Defense Advance Research Project Agency Alfalfa Field
Unable to display preview. Download preview PDF.
- Michalski, R., Baskin, A., Borodkin, S., Boulanger, A., Channic, T., Seyler, M., Reinke, R., Uhrik, C., A Technical Description of the ADVISE. 1 Meta-Expert System, Internal Report, Intelligent System Group, Dept. of Computer Science, University of Illinois, 1986.Google Scholar
- Borror, Delong, Triplehorn, Introduction to Agricultural Entomology, 1976.Google Scholar
- Silver, B., Using Meta-Level Inference to Constrain Search and to Learn Strategies in Equation Solving, Ph.D. Dissertation, Dept. of Artificial Intelligence, University of Edinburgh, 1984.Google Scholar
- Baskin, A., Combining Deterministic and Non-Deterministic Rule Scheduling in an Expert System, Symposium on Computer Applications in Medical Care, 1986.Google Scholar
- Reinke, R., PLANT/ds: An Expert System for Diagnosis of Soybean Diseases, Dept. of Computer Science Report UIUCDCS-F-83-912, University of Illinois, Urbana, Illinois, 1983.Google Scholar
- Boulanger, A., The Expert System PLANT/cd, M.S. Thesis, Dept. of Computer Science Report UIUCDCS-R-83-1134, University of Illinois, Urbana, Illinois, 1983.Google Scholar
- Chilausky, R., and Michalski, R., Knowledge acquisition by encoding rules versus computer induction from examples: case study involving soybean pathology,International Journal for Man-Machine Studies, 12 (1980).Google Scholar