Self-organizing maps for storage and transfer of knowledge in reinforcement learning

@article{Karimpanal2019SelforganizingMF,
  title={Self-organizing maps for storage and transfer of knowledge in reinforcement learning},
  author={Thommen George Karimpanal and Roland Bouffanais},
  journal={Adaptive Behavior},
  year={2019},
  volume={27},
  pages={111 - 126}
}
The idea of reusing or transferring information from previously learned tasks (source tasks) for the learning of new tasks (target tasks) has the potential to significantly improve the sample efficiency of a reinforcement learning agent. In this work, we describe a novel approach for reusing previously acquired knowledge by using it to guide the exploration of an agent while it learns new tasks. In order to do so, we employ a variant of the growing self-organizing map algorithm, which is… Expand
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