A value theory of meta-learning algorithms
AAAI(2006)
摘要
We use game theory to analyze meta-learning algorithms. The objective of meta-learning is to determine which algorithm to apply on a given task. This is an instance of a more general problem that consists of allocating knowledge consumers to learning producers. Solving this general problem in the field of meta-learning yields solutions for related fields such as information retrieval and recommender systems.
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关键词
meta-learning algorithm,related field,meta-learning yields solution,general problem,information retrieval,knowledge consumer,recommender system,value theory,game theory
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