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Abstract

This book has investigated learning in a lifelong context. Lifelong learning addresses cases where a learner faces a whole collection of learning tasks over its entire lifetime. If these tasks are appropriately related, knowledge learned in the first n - 1 tasks can be transferred to the n-th task to boost the generalization accuracy. Two special cases of lifelong learning problems have been investigated in this book: lifelong supervised learning and lifelong control learning. In both cases, lifelong learning involves learning at a meta-level, in which whole spaces of appropriate base-level hypotheses are considered. Consequently, learning at the meta-level requires different representations than base-level learning.

Keywords

Action Model Target Function Lifelong Learning Domain Theory Target Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Sebastian Thrun
    • 1
  1. 1.Carnegie Mellon UniversityUSA

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