ICRA'09 Paper Abstract


Paper FrB6.3

Libeau, Benot (CEA), Micaelli, Alain (Commissariat l'Energie Atomique), Sigaud, Olivier (UPMC-Paris 6)

Transfer of Knowledge for a Climbing Virtual Human: A Reinforcement Learning Approach

Scheduled for presentation during the Regular Sessions "Learning and Adaptive Systems - II" (FrB6), Friday, May 15, 2009, 11:10−11:30, Room: 404

2009 IEEE International Conference on Robotics and Automation, May 12 - 17, 2009, Kobe, Japan

This information is tentative and subject to change. Compiled on January 21, 2022

Keywords Learning and Adaptive Systems


In the reinforcement learning literature, transfer is the capability to reuse on a new problem what has been learnt from previous experiences on similar problems. Adapting transfer properties for robotics is a useful challenge because it can reduce the time spent in the first exploration phase on a new problem. In this paper we present a transfer framework adapted to the case of a climbing Virtual Human. We show that our Virtual Human learns faster to climb a wall after having learnt on a different previous wall.



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