Action-based representation discovery in Markov decision processes
This dissertation investigates the problem of representation discovery in discrete Markov decision processes, namely how agents can simultaneously learn representation and optimal control. Previous work on function approximation techniques for MDPs largely employed hand-engineered basis functions. I...
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| Language: | ENG |
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ScholarWorks@UMass Amherst
2009
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| Online Access: | https://scholarworks.umass.edu/dissertations/AAI3380001 |