Scaling Up Category Learning for Language Acquisition in Human-Robot Interaction

@inproceedings{Lopes2007ScalingUC,
  title={Scaling Up Category Learning for Language Acquisition in Human-Robot Interaction},
  author={Lu{\'i}s Seabra Lopes and Aneesh Chauhan},
  year={2007}
}
Motivated by the need to support language-based communication between robots and their human users, as well as grounded symbolic reasoning, this paper presents a learning architecture that can be used by robotic agents for long-term and open-ended category acquisition. In this learning architecture, multiple object representations and multiple classifiers and classifier combinations are used. All learning computations are carried out during the normal execution of the agent, which allows… CONTINUE READING
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