Tuesday, September 9, 2014

ICDL-EpiRob 2014 Paper Preview

How can robots learn their own goals? How can even human babies that which start with no particular goals at hand develop such intentions and the abstractions thereof? In my upcoming ICDL paper I approach this question which has been longstanding (not only) in the field of developmental robotics:
  • Rolf, M., and M. Asada, "Autonomous Development of Goals: From Generic Rewards to Goal and Self Detection", IEEE Int. Conf. Development and Learning and on Epigenetic Robotics, Genoa, 10/2014. (in press)
Abstract — Goals are abstractions that express agents’ intention and allow them to organize their behavior appropriately. How can agents develop such goals autonomously? This paper proposes a conceptual and computational account to this longstanding problem. We argue to consider goals as abstractions of lower-level intention mechanisms such as rewards and values, and point out that goals need to be considered alongside with a detection of the own actions’ effects. Then, both goals and self-detection can be learned from generic rewards. We show experimentally that task-unspecific rewards induced by visual saliency lead to self and goal representations that constitute goal-directed reaching.
In the following weeks I will detail some of the paper's main points here. Stay tuned!

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