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Summary of Learning Models · No Forgetting

  • Ezey M. Dar-Ei
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 29)

Abstract

This chapter covers ‘no forgetting’ learning curve models whose learning curve parameters are determined from field data. However, we must not forget that the purpose for developing the learning curve is ‘prediction’. Consequently, it is essential to develop the learning model as early as possible from the start of data generation. This means that potential learning models should focus on evaluating the least number of parameters compatible with the ‘goodness of fit’. As it turns out, our experience shows that 2-parameter learning curve models are about as ‘accurate’ as models with 3 or more parameters, so consequently this chapter focuses on 2-parameter learning curve models. If one is concerned with fitting a model to large amounts of learning data, then one should not be constrained to working with ‘proposed’ models — rather, one should apply known mathematical techniques for model fitting to data. Nevertheless, three and more parameter learning models are discussed in Section 3.8.

Keywords

Performance Time Learn Model Motor Learning Power Model Learning Parameter 
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

© Springer Science+Business Media New York 2000

Authors and Affiliations

  • Ezey M. Dar-Ei
    • 1
  1. 1.Faculty of Industrial Engineering and ManagementTechnion - Israel Institute of TechnologyHaifaIsrael

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