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2 results

  • 14 - Computational Models of Implicit Learning

  • from Part III - Computational Modeling of Various Cognitive Functionalities and Domains
  • Edited by Ron Sun
  • Book:
    The Cambridge Handbook of Computational Psychology
    Published online:
    05 June 2012
    Print publication:
    28 April 2008, pp 396-421

  • Summary

    This chapter surveys a variety of formal models of categorization, with emphasis on exemplar models. The chapter reviews exemplar models' similarity functions, learning algorithms, mechanisms for exemplar recruitment, formalizations of response probability, and response dynamics. A mutual goal of different formal models is to account for detailed quantitative data from laboratory experiments in categorization. Although a variety of representational formats have been formalized, exemplar models have been especially richly explored by researchers. The chapter discriminates numerous exemplar models to excise their functional components and to examine those components side by side. The main functional components include the computation of similarity, the learning of associations and attention, the recruitment of exemplars, the determination of response probability, and the generation of response times. This dissection revealed a variety of formalizations available for expressing any given psychological process.

  • An overview of robot force control

  • Ganwen Zeng, Ahmad Hemami
  • Journal:
    Robotica / Volume 15 / Issue 5 / September 1997
    Published online by Cambridge University Press:
    01 September 1997, pp. 473-482

  • This paper reports on the existing robot force control algorithms and their composition based on the review of 75 papers on this subject. The objective is to provide a pragmatic exposition with speciality on their differences and different application conditions, and to give a guide of the existing robot force control algorithms. The previous work can be categorized into discussion, design and/or application of fundamental force control techniques, stability analysis of the various control algorithms, and the advanced methods. Advanced methods combine the fundamental force control techniques with advanced control algorithms such as adaptive, robust and learning control strategies.