Discretization and Approximation Methods for Reinforcement Learning of Highly Reconfigurable Systems
There are a number of techniques that are used to solve reinforcement learning problems, but very few that have been developed for and tested on highly reconfigurable systems cast as reinforcement learning problems. Reconfigurable systems refers to a vehicle (air, ground, or water) or collection of...
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| Format: | Others |
| Language: | English |
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2010
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| Online Access: | http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7421 |