60 search results - page 1 / 12 » Iteratively Extending Time Horizon Reinforcement Learning |
ECML
2003
Springer
13 years 10 months ago
2003
Springer
AAAI
1997
13 years 6 months ago
1997
This paper steps back from the standard infinite horizon formulation of reinforcement learning problems to consider the simpler case of finite horizon problems. Although finite ho...
ICML
2003
IEEE
13 years 10 months ago
2003
IEEE
Shaping can be an effective method for improving the learning rate in reinforcement systems. Previously, shaping has been heuristically motivated and implemented. We provide a for...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
We cast model-free reinforcement learning as the problem of maximizing the likelihood of a probabilistic mixture model via sampling, addressing both the infinite and finite horizo...
AIPS
2006
13 years 6 months ago
2006
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...