181 search results - page 1 / 37 » State Space Reduction For Hierarchical Reinforcement Learnin... |
FLAIRS
2004
13 years 5 months ago
2004
er provides new techniques for abstracting the state space of a Markov Decision Process (MDP). These techniques extend one of the recent minimization models, known as -reduction, ...
NCI
2004
13 years 5 months ago
2004
This paper describes a method for hierarchical reinforcement learning in which high-level policies automatically discover subgoals, and low-level policies learn to specialize for ...
AR
2008
13 years 4 months ago
2008
The existing reinforcement learning methods have been seriously suffering from the curse of dimension problem especially when they are applied to multiagent dynamic environments. ...
ROBOCUP
2007
Springer
13 years 10 months ago
2007
Springer
The existing reinforcement learning approaches have been suffering from the curse of dimension problem when they are applied to multiagent dynamic environments. One of the typical...
ICMLA
2009
13 years 2 months ago
2009
This paper describes a novel real-world reinforcement learning application: The Neuro Slot Car Racer. In addition to presenting the system and first results based on Neural Fitted...