Transfer in Reinforcement Learning Domains
In reinforcement learning (RL) problems, learning agents sequentially execute actions with the goal of maximizing a reward signal. The RL framework has gained popularity with the development of algorithms capable of mastering increasingly complex problems, but learning difficult tasks is often slow...
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| Format: | Electronic |
| Language: | English |
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Berlin, Heidelberg :
Springer Berlin Heidelberg,
2009.
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| Series: | Studies in Computational Intelligence,
216 |
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| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-01882-4 |