A symbol's role in learning low-level control functions.
This thesis demonstrates how the power of symbolic processing can be exploited in the learning of low level control functions. It proposes a novel hybrid architecture with a tight coupling between a variant of symbolic planning and reinforcement learning. This architecture combines the strengths of...
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University of Ottawa (Canada)
2009
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| Online Access: | http://hdl.handle.net/10393/8886 http://dx.doi.org/10.20381/ruor-16036 |