학술논문
Transfer of knowledge for a climbing Virtual Human: A reinforcement learning approach
Document Type
Conference
Author
Source
2009 IEEE International Conference on Robotics and Automation Robotics and Automation, 2009. ICRA '09. IEEE International Conference on. :2119-2124 May, 2009
Subject
Language
ISSN
1050-4729
Abstract
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 (VH). We show that our VH learns faster to climb a wall after having learnt on a different previous wall.