Deep reinforcement learning for physical agents

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  • 2021

    Few-shot model-based adaptation in noisy conditions

    Arndt, K., Ghadirzadeh, A., Hazara, M. & Kyrki, V., Apr 2021, In: IEEE Robotics and Automation Letters. 6, 2, p. 4193-4200 8 p., 9384205.

    Research output: Contribution to journalArticleScientificpeer-review

    Open Access
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    42 Downloads (Pure)
  • 2020

    Meta Reinforcement Learning for Sim-to-real Domain Adaptation

    Arndt, K., Hazara, M., Ghadirzadeh, A. & Kyrki, V., 2020, Proceedings of the IEEE Conference on Robotics and Automation, ICRA 2020. IEEE, p. 2725-2731 7 p. 9196540. (IEEE International Conference on Robotics and Automation).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    4 Citations (Scopus)
  • 2019

    Affordance Learning for End-to-End Visuomotor Robot Control

    Hamalainen, A., Arndt, K., Ghadirzadeh, A. & Kyrki, V., 1 Nov 2019, Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019. IEEE, p. 1781-1788 8 p. 8968596. (Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access
    4 Citations (Scopus)
  • Meta-Learning for Multi-objective Reinforcement Learning

    Chen, X., Ghadirzadeh, A., Björkman, M. & Jensfelt, P., 2019, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2019. IEEE, p. 977-983 7 p. (Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems).

    Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

    Open Access