Chapter

Creating Brain-Like Intelligence

Volume 5436 of the series Lecture Notes in Computer Science pp 139-150

Towards Learning by Interacting

  • Britta WredeAffiliated withApplied Computer Science, Bielefeld UniversityInstitute for Cognition and Robotics (CoR-Lab)
  • , Katharina J. RohlfingAffiliated withApplied Computer Science, Bielefeld UniversityInstitute for Cognition and Robotics (CoR-Lab)
  • , Marc HanheideAffiliated withApplied Computer Science, Bielefeld UniversityInstitute for Cognition and Robotics (CoR-Lab)
  • , Gerhard SagererAffiliated withApplied Computer Science, Bielefeld UniversityInstitute for Cognition and Robotics (CoR-Lab)

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Abstract

Traditional robotics has treated the question of learning as a one way process: learning algorithms, especially imitation learning approaches, are based on observing and analysing the environment before carrying out the ‘learned’ action. In such scenarios the learning situation is restricted to uni-directional communication.

However, insights into the process of infant learning more and more reveal that interaction plays a major role in transferring relevant information to the learner. For example, in learning situations, the interactive situation has the potential to highlight parts of an action by linguistic and non-linguistic features and thus to guide the attention of the learner to those aspects that the tutor deems relevant for her current state of mind.

We argue that learning necessarily needs to be embedded in an interactive situation and that developmental robotics, in order to model engagement in interaction, needs to take the communicative context into account. We further propose that such an approach necessarily needs to take three aspects into account: (1) multi-modal integration at all processing levels (2) derivation of top-down strategies from bottom-up processes and (3) integration of single modules into an interactive system in order to facilite the first two desiderata.