28 search results - page 4 / 6 » The MAXQ Method for Hierarchical Reinforcement Learning |
GECCO
2008
Springer
13 years 9 months ago
2008
Springer
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
ICML
2003
IEEE
14 years 9 months ago
2003
IEEE
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
GECCO
2005
Springer
14 years 2 months ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
IROS
2006
IEEE
14 years 2 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 11 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...