26 search results - page 5 / 6 » Subgoal Discovery for Hierarchical Reinforcement Learning Us... |
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
ICRA
2006
IEEE
13 years 11 months ago
2006
IEEE
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...
IJCAI
2007
13 years 7 months ago
2007
Learning capabilities of computer systems still lag far behind biological systems. One of the reasons can be seen in the inefficient re-use of control knowledge acquired over the...
IROS
2006
IEEE
13 years 11 months ago
2006
IEEE
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
AAAI
2008
13 years 8 months ago
2008
Hierarchical state decompositions address the curse-ofdimensionality in Q-learning methods for reinforcement learning (RL) but can suffer from suboptimality. In addressing this, w...