article · 2007

Speedup Learning

Alan Fern

Cited by 0Abstract and details only

Abstract

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 solved problems. The output is knowledge that the problem solver can exploit to find solutions more quickly than before learning without seriously effecting solution quality. The most distinctive feature of speedup learning, compared to 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 practically efficient problem solvers for combinatorially

Cite this paper

APA 7

Fern, A. (2007). Speedup Learning.

MLA 9

Fern, Alan. “Speedup Learning.” 2007.

Chicago

Fern, Alan. 2007. “Speedup Learning.”

Harvard

Fern, A. (2007) ‘Speedup Learning’.

BibTeX

@article{fern2007speedup,
  title = {{Speedup Learning}},
  author = {Fern, Alan},
  year = {2007}
}

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