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Self-organizing developmental reinforcement learning

Alain Dutech 1 
1 MAIA - Autonomous intelligent machine
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : This paper presents a developmental reinforcement learning framework aimed at exploring rich, complex and large sensorimotor spaces. The core of this architecture is made of a function approximator based on a Dynamic Self-Organizing Map (DSOM). The life-long online learning property of the DSOM allows us to take a developmental approach to learning a robotic task: the perception and motor skills of the robot can grow in richness and complexity during learning. This architecture is tested on a robotic task that looks simple but is still challenging for reinforcement learning.
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Submitted on : Thursday, June 7, 2012 - 2:33:36 PM
Last modification on : Saturday, June 25, 2022 - 7:46:32 PM
Long-term archiving on: : Thursday, December 15, 2016 - 12:24:49 PM


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  • HAL Id : hal-00705350, version 1



Alain Dutech. Self-organizing developmental reinforcement learning. International Conference on Simulated Animal Behavior, 2012, Odense, Denmark. ⟨hal-00705350⟩



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