Self segmentation of sequences
| Abstract | chical reinforcement learning that does not rely on a pri ori hierarchical structures Thus the approach deals with a more di cult problem compared with existing work It in volves learning to segment sequences to create hierarchical structures based on reinforcement received during task ex ecution with di erent levels of control communicating with each other through sharing reinforcement estimates obtained by each others The algorithm segments sequences to re duce non Markovian temporal dependencies to facilitate the learning of the overall task Initial experiments demon strated the basic promise of the approach.. | |||||||||
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Similar books and articlesC. P. Schnorr & P. Fuchs (1977). General Random Sequences and Learnable Sequences. Journal of Symbolic Logic 42 (3):329-340.
Peter F. Dominey (1997). Reducing Problem Complexity by Analogical Transfer. Behavioral and Brain Sciences 20 (1):71-72.
Reiko Yakushijin & Robert A. Jacobs (2011). Are People Successful at Learning Sequences of Actions on a Perceptual Matching Task? Cognitive Science 35 (5):939-962.
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