A Comparative Utility Analysis of Case-Based Reasoning and Control-Rule Learning Systems

The utility problem in learning systems occurs when knowledge learned in an attempt to improve a system’s performance degrades performance instead. We present a methodology for the analysis of utility problems which uses computational models of problem solving systems to isolate the root causes of a utility problem, to detect the threshold conditions under which the problem will arise, and to design strategies to eliminate it. We present models of case-based reasoning and control-rule learning systems and compare their performance with respect to the swamping utility problem. Our analysis suggests that case-based reasoning systems are more resistant to the utility problem than control-rule learning systems.

Read the paper:

A Comparative Utility Analysis of Case-Based Reasoning and Control-Rule Learning Systems

by Anthony Francis, Ashwin Ram

8th European Conference on Machine Learning (ECML-95), Crete, Greece, April 1995
www.cc.gatech.edu/faculty/ashwin/papers/er-95-02.pdf
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