17 search results - page 1 / 4 » Hierarchical Reinforcement Learning with the MAXQ Value Func... |
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
JAIR
2000
13 years 4 months ago
2000
ICML
2002
IEEE
14 years 5 months ago
2002
IEEE
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
PRICAI
2000
Springer
13 years 8 months ago
2000
Springer
This paper presents the CQ algorithm which decomposes and solves a Markov Decision Process (MDP) by automatically generating a hierarchy of smaller MDPs using state variables. The ...
PKDD
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. Innovations such as optimistic exploration, function approximation, and hierarchical decomposition have helped scale reinforcement learning to more complex environments, ...