An Algorithm for Self-Motivated Hierarchical Sequence Learning

Olivier L. Georgeon 1 Jonathan Morgan Frank Ritter
1 SILEX - Supporting Interaction and Learning by Experience
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : This work demonstrates a mechanism that autonomously organizes an agent’s sequential behavior. The behavior organization is driven by pre-defined values associated with primitive behavioral patterns. The agent learns increasingly elaborated behaviors through its interactions with its environment. These learned behaviors are gradually organized in a hierarchy that reflects how the agent exploits the hierarchical regularities afforded by the environment. To an observer, the agent thus appears to exhibit basic self- motivated, sensible, and learning behavior to fulfill its inborn predilections. As such, this work illustrates Piaget’s theories of early-stage developmental learning.
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Communication dans un congrès
International Conference on Cognitive Modeling, Aug 2010, Philadelphia, PA, United States. pp.73-78, 2010
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https://hal.archives-ouvertes.fr/hal-01381588
Contributeur : Équipe Gestionnaire Des Publications Si Liris <>
Soumis le : vendredi 14 octobre 2016 - 14:49:40
Dernière modification le : mercredi 27 septembre 2017 - 09:46:02

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  • HAL Id : hal-01381588, version 1

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Olivier L. Georgeon, Jonathan Morgan, Frank Ritter. An Algorithm for Self-Motivated Hierarchical Sequence Learning. International Conference on Cognitive Modeling, Aug 2010, Philadelphia, PA, United States. pp.73-78, 2010. 〈hal-01381588〉

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