Skip to main content
Article thumbnail
Location of Repository

A Method for Multistrategy Task-Adaptive Learning Based on Plausible Justifixations

By R. S. Michalski

Abstract

Multistrategy task-adaptive learning (MTL) comprises a class of methods in which the learner determines by itself which strategy or combination of strategies is most appropriate for a given learning task defined by the learner's goal, the leamer's background knowledge (BK) and the input to the learning process. The paper presents a MTL method which is based on building a plausible justification that the learner's input is a consequence of its BK. The method assumes a general learning goal of deriving any useful knowledge from a given input and integrates dynamically a whole range of learning sategies. It also behaves as a singlestrategy method when the relationship between the input and the BK satisfies the requirements of the single-strategy method, and the general learning goal of the MTL method is specialized to the goal of the single-strategy method

Publisher: Morgan Kaufmann
Year: 1991
OAI identifier: oai:CiteSeerX.psu:10.1.1.19.9674
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.mli.gmu.edu/papers/... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.