Material Detail
Poster Spotlights: Automated Discovery of Options in Factored Reinforcement Learning
This video was recorded at 26th International Conference on Machine Learning (ICML), Montreal 2009. Factored Reinforcement Learning (FRL) is a method to solve Factored Markov Decision Processes when the structure of the transition and reward functions of the problem must be learned. In this paper, we present TeXDYNA, an algorithm that combines the abstraction techniques of Semi-Markov Decision Processes to perform the automatic hierarchical decomposition of the problem with an FRL method. The algorithm is evaluated on the taxi problem.
Quality
- User Rating
- Comments
- Learning Exercises
- Bookmark Collections
- Course ePortfolios
- Accessibility Info
More about this material
- Mobile Compatibility:
- Not specified at this time
- Language:
- English
- Cost Involved:
- No
- Source Code Available:
- No
- Creative Commons:
-
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
