Macolm Ryan developed a hierarchical reinforcement learning system for acquiring agent behaviours. High-level plans were created by a symbolic planner but low-level actions were learned by reinforcement learning. Symbolic plans could be modified by learning in an ILP style. Malcolm is a research fellow with the ARC Centre of Excellence for Autonomous Systems.
Claude Sammut
School of Computer Science and Engineering, UNSW Australia
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