Learning from History for Behavior-Based Mobile Robots in Non-Stationary Conditions

@article{Michaud1998LearningFH,
  title={Learning from History for Behavior-Based Mobile Robots in Non-Stationary Conditions},
  author={François Michaud and Maja J. Mataric},
  journal={Machine Learning},
  year={1998},
  volume={31},
  pages={141-167}
}
  • François Michaud, Maja J. Mataric
  • Published in Machine Learning 1998
  • Computer Science
  • Learning in the mobile robot domain is a very challenging task, especially in non-stationary conditions. The behavior-based approach has proven to be useful in making mobile robots work in real-world situations. Since the behaviors are responsible for managing the interactions between the robots and its environment, observing their use can be exploited to model these interactions. In our approach, the robot is initially given a set of “behavior-producing” modules to choose from, and the… CONTINUE READING

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