Encyclopedia of Machine Learning

2010 Edition
| Editors: Claude Sammut, Geoffrey I. Webb

Speedup Learning

  • Alan Fern
Reference work entry
DOI: https://doi.org/10.1007/978-0-387-30164-8_772


Speedup learning is a branch of machine learning that studies learning mechanisms for speeding up problem solvers based on problem-solving experience. The input to a speedup learner typically consists of observations of prior problem-solving experience, which may include traces of the problem solver’s operations and/or solutions to solve the problems. The output is knowledge that the problem solver can exploit to find solutions more quickly than before learning without seriously effecting the solution quality. The most distinctive feature of speedup learning, compared with most branches of machine learning, is that the learned knowledge does not provide the problem solver with the ability to solve new problem instances. Rather, the learned knowledge is intended solely to facilitate faster solution times compared to the solver without the knowledge.

Motivation and Background

Much of the work in computer science and especially artificial intelligence aims at developing...

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Recommended Reading

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Alan Fern

There are no affiliations available