Artificial Intelligence Review

, Volume 18, Issue 2, pp 77–95

A Perspective View and Survey of Meta-Learning

  • Ricardo Vilalta
  • Youssef Drissi
Article

DOI: 10.1023/A:1019956318069

Cite this article as:
Vilalta, R. & Drissi, Y. Artificial Intelligence Review (2002) 18: 77. doi:10.1023/A:1019956318069

Abstract

Different researchers hold different views of what the term meta-learning exactlymeans. The first part of this paper provides our own perspective view in which the goal isto build self-adaptive learners (i.e. learning algorithms that improve their bias dynamicallythrough experience by accumulating meta-knowledge). The second part provides a survey ofmeta-learning as reported by the machine-learning literature. We find that, despite differentviews and research lines, a question remains constant: how can we exploit knowledge aboutlearning (i.e. meta-knowledge) to improve the performance of learning algorithms? Clearlythe answer to this question is key to the advancement of the field and continues being thesubject of intensive research.

classification inductive learning meta-knowledge 

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Ricardo Vilalta
    • 1
  • Youssef Drissi
    • 1
  1. 1.IBM T.J. Watson Research CenterHawthorneUSA