Encoding and Combining Knowledge to Speed up Reinforcement Learning

Brys, Tim

Encoding and Combining Knowledge to Speed up Reinforcement Learning

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 4347-4347.

Abstract

Reinforcement learning algorithms typically require too many `trial-and-error' experiences before reaching a desirable behaviour. A considerable amount of ongoing research is focused on speeding up this learning process by using external knowledge. We contribute in several ways, proposing novel approaches to transfer learning and learning from demonstration, as well as an ensemble approach to combine knowledge from various sources.

Tim Brys. 2015. Encoding and Combining Knowledge to Speed up Reinforcement Learning. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 4347–4347. https://ijcai.org/proceedings/2015/621

@inproceedings{ijcai2015p621,
  title     = {Encoding and Combining Knowledge to Speed up Reinforcement Learning},
  author    = {Brys, Tim},
  booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-15}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Qiang Yang and Michael Wooldridge},
  pages     = {4347--4347},
  year      = {2015},
  month     = {7},
  note      = {Doctoral Consortium},
  url       = {https://ijcai.org/proceedings/2015/621},
}

TY  - CPAPER
TI  - Encoding and Combining Knowledge to Speed up Reinforcement Learning
AU  - Brys, Tim
T2  - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2015
SP  - 4347
EP  - 4347
UR  - https://ijcai.org/proceedings/2015/621
ER  -