Accession Number:

ADA440280

Title:

Intrinsically Motivated Reinforcement Learning

Descriptive Note:

Corporate Author:

MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE

Report Date:

2005-01-01

Pagination or Media Count:

9.0

Abstract:

Psychologists call behavior intrinsically motivated when it is engaged in for its own sake rather than as a step toward solving a specific problem of clear practical value. But what we learn during intrinsically motivated behavior is essential for our development as competent autonomous entities able to efficiently solve a wide range of practical problems as they arise. In this paper we present initial results from a computational study of intrinsically motivated reinforcement learning aimed at allowing artificial agents to construct and extend hierarchies of reusable skills that are needed for competent autonomy.

Subject Categories:

  • Psychology
  • Numerical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE