A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Knowledge acquisition for expert systems
Knowledge acquisition for expert systems
Second generation expert systems
Future Generation Computer Systems
Expert systems: the next challenge for managers
Sloan Management Review
Artificial Intelligence
Knowledge extraction through learning from examples
Machine learning: a guide to current research
Current developments in expert systems
Proceedings of the Second Australian Conference on Applications of expert systems
Automatic synthesis and compression of cardiological knowledge
Machine intelligence 11
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
Machine Learning
The art of artificial intelligence: I. Themes and case studies of knowledge engineering
The art of artificial intelligence: I. Themes and case studies of knowledge engineering
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First generation expert systems rely on the use of surface knowledge, such as associational or heuristic. Second generation technology is characterized by two additional features: deep knowledge and machine learning. Three second generation methods for knowledge acquisition are reviewed: learning rules from examples, model-based rule learning, and semi-automatic model acquisition. The man-machine process of acquiring and refining knowledge extends the role of expert systems to expert support systems, since both man and machine learn through repeated knowledge refinement cycles. Explanation of solutions and of the knowledge base itself is crucial for this man-machine learning process. An extended expert system shell schema is presented that includes a knowledge acquisition and a knowledge explanation module.