Learning State and Action Abstractions for Effective and Efficient Planning
An autonomous agent should make good decisions quickly. These two considerations --- effectiveness and efficiency --- are especially important, and often competing, when an agent plans to make decisions sequentially in long-horizon tasks. Unfortunately, planning directly in the state and action spac...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2022
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| Online Access: | https://hdl.handle.net/1721.1/145150 |