Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning

Summary: Pending
This paper was given to Warfield by the author, on a visit to the GMU office December 28, 1998. Michalski is at Center for Artificial Intelligence, School of Information Technology,George Mason University worked under A.P. Sage to his regret. ABSTRACT: tHERE IS NEED FOR A GENERAL CONCEPTUAL FRAMEWORK that would explain interrelationships between machine learning methods. The author's theory views learning as a goal oriented process of modifying the learner's knowledge by exploring the learner's experience. - using deduction, induction or analogy. the theory provides a basis for MTL (MULTISTRATEGY TASK-ADAPTIVE LEARNING) AIMS AT SYNERGISTICALLY INTEGRATING A WIDE RANGE OF INFERENTIAL LEARNING STRATEGIES, SUCH AS EMPIRICAL AND CONSTRUCTIVE INDUCTIVE GENERALIZATION, DEDUCTIVE GENERALIZATION, ABDUCTIVE DERIVATION, ABSTRACTION, SIMILIZATION AND OTHERS.

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  • Description: Electronic reproduction
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