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AI
1999
Springer

Introspective Multistrategy Learning: On the Construction of Learning Strategies

11 years 5 months ago
Introspective Multistrategy Learning: On the Construction of Learning Strategies
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system designer who analyzes the learning task and implements the appropriate algorithm or sequence of algorithms for that task. We propose a solution to this problem which enables an AI system with a library of machine learning algorithms to select and sequence appropriate algorithms autonomously. Furthermore, instead of relying on the system designer or user to provide a learning goal or target concept to the learning system, our method enables the system to determine its learning goals based on analysis of its successes and failures at the performance task. The method involves three steps: Given a performance failure, the learner examines a trace of its reasoning prior to the failure to diagnose what went wrong (blame assignment); given the resultant explanation of the reasoning failure, the learner posts explici...
Michael T. Cox, Ashwin Ram
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 1999
Where AI
Authors Michael T. Cox, Ashwin Ram
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