86 search results - page 10 / 18 » Evolution of reward functions for reinforcement learning |
ICML
2003
IEEE
16 years 15 days ago
2003
IEEE
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
NIPS
2001
15 years 1 months ago
2001
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
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ICML
1999
IEEE
16 years 15 days ago
1999
IEEE
Many interesting problems, such as power grids, network switches, and tra c ow, that are candidates for solving with reinforcement learningRL, alsohave properties that make distri...
IJCAI
2007
15 years 1 months ago
2007
In recent years, there has been a growing interest in using rich representations such as relational languages for reinforcement learning. However, while expressive languages have ...
AIPS
2006
15 years 1 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 ...