Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution

@article{Rothfuss2018DeepEM,
  title={Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution},
  author={Jonas Rothfuss and Fabio Ferreira and Eren Erdal Aksoy and You Zhou and Tamim Asfour},
  journal={IEEE Robotics and Automation Letters},
  year={2018},
  volume={3},
  pages={4007-4014}
}
We present a novel deep neural network architecture for representing robot experiences in an episodic-like memory that facilitates encoding, recalling, and predicting action experiences. Our proposed unsupervised deep episodic memory model as follows: First, encodes observed actions in a latent vector space and, based on this latent encoding, second, infers most similar episodes previously experienced, third, reconstructs original episodes, and finally, predicts future frames in an end-to-end… CONTINUE READING
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