Deep Reinforcement Learning for a Humanoid Robot Soccer Player-Reference-Cited by-同舟云学术

Deep Reinforcement Learning for a Humanoid Robot Soccer Player

Published:2021-06-26 Issue:3 Volume:102 Page:
ISSN:0921-0296
Container-title:Journal of Intelligent & Robotic Systems
language:en
Short-container-title:J Intell Robot Syst

Author:

da Silva Isaac Jesus^ORCID,Perico Danilo Hernani,Homem Thiago Pedro Donadon,da Costa Bianchi Reinaldo Augusto

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Industrial and Manufacturing Engineering,Mechanical Engineering,Control and Systems Engineering,Software

Link

https://link.springer.com/content/pdf/10.1007/s10846-021-01333-1.pdf

Reference39 articles.

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2. Lim, J., Lee, I., Shim, I., Jung, H., Joe, H.M., Bae, H., Sim, O., Oh, J., Jung, T., Shin, S., et al.: Robot system of drc-hubo+ and control strategy of team kaist in darpa robotics challenge finals. Journal of Field Robotics 34(4), 802–829 (2017)

3. Jumel, F., Saraydaryan, J., Leber, R., Matignon, L., Lombardi, E., Wolf, C., Simonin, O.: Context aware robot architecture, application to the robocup@ home challenge. In: Robocup Symposium (2018)

4. Perico, D.H., Silva, I.J, Vilão, C.O. JR, Homem, T.P.D., Destro, R.C, Tonidandel, F., Bianchi, R.A.C.: Newton: a high level control humanoid robot for the robocup soccer kidsize league. In: Robotics, pp 53–73. Springer (2014)

5. Kempka, M., Wydmuch, M., Runc, G., Toczek, J., Jaśkowski, W.: Vizdoom: a doom-based ai research platform for visual reinforcement learning. arXiv:1605.02097 (2016)

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