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Curiosity driven reinforcement learning for motion planning on humanoids.

Front Neurorobot

January 2014

Dalle Molle Institute for Artificial Intelligence Lugano, Switzerland ; Facoltà di Scienze Informatiche, Università della Svizzera Italiana Lugano, Switzerland ; Dipartimento Tecnologie Innovative, Scuola Universitaria Professionale della Svizzera Italiana Manno, Switzerland.

Article Synopsis
  • Previous research on artificial curiosity (AC) primarily revolves around basic theories and is often limited to simple experimental scenarios.
  • The study introduces a curious agent embodied in the complex iCub humanoid robot, utilizing a novel reinforcement learning framework that combines both reactive control and high-level curiosity-driven exploration.
  • This is the first instance of an embodied curious agent capable of real-time motion planning, demonstrating intelligent exploration by learning Markov models and showing interest in physical constraints and environmental objects.
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