Known as OCCAM, the system uses theory-driven learning when new experiences conform to common patterns of causal relationships, empirical learning to learn from novel experiences, and explanation-based learning when there is sufficient existing knowledge to explain why a new outcome occurred. Together these learning methods construct a hierarchical organized memory of causal relationships. As such, OCCAM is the first learning system with the ability to acquire, via empirical learning, the background knowledge required for explanation-based learning.
Please note: This program runs on common lisp.
|Publisher:||Taylor & Francis|
|Sold by:||Barnes & Noble|
|File size:||9 MB|
Table of Contents
Contents: Introduction. What OCCAM Is Up Against. Similarity-Based Learning in OCCAM. Theory-Driven Learning in OCCAM. Explanation-Based Learning in OCCAM. Integration of Learning Methods. Experiments in Integrated Learning. Future Directions and Conclusions. Appendices: Data Listing. Program Traces. Prolog OCCAM. OCCAM's Generalization Rules. Listing of Economic Sanction Incidents.