Solution of an Optimal Routing Problem by Reinforcement Learning with Generalization Ability

Author:

Iima Hitoshi1,Oonishi Hiroya1

Affiliation:

1. Kyoto Institute of Technology

Publisher

Institute of Electrical Engineers of Japan (IEE Japan)

Subject

Electrical and Electronic Engineering

Reference10 articles.

1. (1) V. Mnih, K. Kavukcuoglu, D. Silver, et al.: “Human-level control through deep reinforcement learning”, Nature, Vol. 518, pp. 529-533 (2015)

2. (2) D. Silver, J. Schrittwieser, K. Simonyan, et al.: “Mastering the game of Go without human knowledge”, Nature, Vol. 550, pp. 354-359 (2017)

3. (4) N. Kotani : “Knowledge Selection based on Value in Transfer Learning”, Transactions of the Institute of Systems, Control and Information Engineers, Vol. 28, No. 6, pp. 275-283 (2015) (in Japanese)

4. (5) O. Anschel, N. Baram, and N. Shimk : “Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning”, Proceedings of International Conference on Machine Learning (2017)

5. (6) H. Oonishi and H. Iima : “Improving generalization ability in a puzzle game using reinforcement learning”, Proceedings of IEEE Conference on Computational Intelligence and Games, pp. 232-239 (2017)

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