Learning skills from play: Artificial curiosity on a Katana robot arm

Artificial curiosity tries to maximize learning progress. We apply this concept to a physical system. Our Katana robot arm curiously plays with wooden blocks, using vision, reaching, and grasping. It is intrinsically motivated to explore its world. As a by-product, it learns how to place blocks stably, and how to stack blocks.

[1]  Richard Bellman,et al.  Adaptive Control Processes: A Guided Tour , 1961, The Mathematical Gazette.

[2]  James F. Christie,et al.  Play and Early Childhood Development , 1987 .

[3]  F. Wardle Guest Editorial: Getting Back to the Basics of Children's Play. , 1987 .

[4]  S. Hochreiter,et al.  REINFORCEMENT DRIVEN INFORMATION ACQUISITION IN NONDETERMINISTIC ENVIRONMENTS , 1995 .

[5]  L. E. Berk,et al.  Scaffolding Children's Learning: Vygotsky and Early Childhood Education. NAEYC Research into Practice Series. Volume 7. , 1995 .

[6]  S. Kontos Preschool teachers’ talk, roles, and activity settings during free play , 1999 .

[7]  V. Vovk Competitive On‐line Statistics , 2001 .

[8]  Jean-Yves Bouguet,et al.  Camera calibration toolbox for matlab , 2001 .

[9]  Peter Auer,et al.  Using Confidence Bounds for Exploitation-Exploration Trade-offs , 2003, J. Mach. Learn. Res..

[10]  Ronen I. Brafman,et al.  R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning , 2001, J. Mach. Learn. Res..

[11]  Michail G. Lagoudakis,et al.  Least-Squares Policy Iteration , 2003, J. Mach. Learn. Res..

[12]  Claudio Gentile,et al.  Incremental Algorithms for Hierarchical Classification , 2004, J. Mach. Learn. Res..

[13]  Manfred K. Warmuth,et al.  Relative Loss Bounds for On-Line Density Estimation with the Exponential Family of Distributions , 1999, Machine Learning.

[14]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[15]  Jürgen Schmidhuber,et al.  Developmental robotics, optimal artificial curiosity, creativity, music, and the fine arts , 2006, Connect. Sci..

[16]  Michael L. Littman,et al.  Online Linear Regression and Its Application to Model-Based Reinforcement Learning , 2007, NIPS.

[17]  Claudio Gentile,et al.  Robust bounds for classification via selective sampling , 2009, ICML '09.

[18]  Jürgen Schmidhuber,et al.  Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990–2010) , 2010, IEEE Transactions on Autonomous Mental Development.

[19]  Jürgen Schmidhuber,et al.  AutoIncSFA and vision-based developmental learning for humanoid robots , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.