Automatic Action Space Curriculum Learning with Dynamic Per-Step Masking
Author:
Affiliation:
1. Hitachi Ltd,Center for Technology Innovation, R&D Group,Robotics Research Department,Japan
2. Graduate School of Fundamental Science and Engineering, Waseda University,Department of Intermedia Art and Science,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10260321/10260291/10260397.pdf?arnumber=10260397
Reference19 articles.
1. Curriculum-based Offline Network Training for Improvement of Peg-in-hole Task Performance for Holes in Concrete
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3. Dropout: A simple way to prevent neural networks from overfitting;srivastava;Journal of Machine Learning Research,2014
4. Learning and development in neural networks: the importance of starting small
5. Automatic goal generation for reinforcement learning agents;florensa;Proceedings of the 35th International Conference on Machine Learning ser Proceedings of Machine Learning Research,2018
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