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Long Term Learning and Online Robot Behavior Adaptation for Individuals with Physical and Cognitive Impairments

  • Adriana Tapus
  • Cristian Tapus
  • Maja Matarić
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 62)

Abstract

In this paper, we present an online adaptation approach and a long-term learning approach for socially assistive robotic (SAR) systems that aim to provide customized help protocols through motivation, encouragements, and companionship to users suffering from physical and/or cognitive changes related to stroke, aging and Alzheimer’s disease.

Keywords

Reward Function Social Robot Game Level Term Learn Assistive Robotic System 
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-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Adriana Tapus
    • 1
  • Cristian Tapus
    • 2
  • Maja Matarić
    • 3
  1. 1.ENSTA-ParisTechParisFrance
  2. 2.Research Scientist at Google Inc.Mountain ViewUSA
  3. 3.Computer Science DepartmentUniversity of Southern CaliforniaLos AngelesUSA

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