TY - STD TI - Rahman MDM, Rashid SMH, Hassan KMR, Hossain MM. Comparison of different control theories on a two wheeled self balancing robot. In: AIP conference proceedings, 1980; 1: 060005. 2018. https://aip.scitation.org/doi/abs/10.1063/1.5044373. UR - https://aip.scitation.org/doi/abs/10.1063/1.5044373 ID - ref1 ER - TY - JOUR AU - Tai, L. AU - Liu, M. PY - 2016 DA - 2016// TI - Mobile robots exploration through cnn-based reinforcement learning JO - Robot. Biomim. VL - 3 UR - https://doi.org/10.1186/s40638-016-0055-x DO - 10.1186/s40638-016-0055-x ID - Tai2016 ER - TY - STD TI - Zamora I, Lopez NG, Vilches VM, Cordero AH. Extending the openai gym for robotics: a toolkit for reinforcement learning using ROS and gazebo. CoRR, vol. abs/1608.05742, 2016. http://arxiv.org/abs/1608.05742. UR - http://arxiv.org/abs/1608.05742 ID - ref3 ER - TY - STD TI - Tran LD, Cross CD, Motter MA, Neilan JH, Qualls G, Rothhaar PM, Trujillo A, Allen BD. Reinforcement learning with autonomous small unmanned aerial vehicles in cluttered environments. In: 15th AIAA aviation technology, integration, and operations conference, Jun 2015. https://doi.org/10.2514/6.2015-2899. UR - https://doi.org/10.2514/6.2015-2899 ID - ref4 ER - TY - STD TI - Sereda V. Machine learning for robots with ros, Master’s thesis, Maynooth University. Maynooth, Co. Kidare, 2017. ID - ref5 ER - TY - STD TI - Border R. Learning to save lives: Using reinforcement learning with environment features for efficient robot search. White Paper, University of Oxford, 2015. ID - ref6 ER - TY - STD TI - Watkins CJ. Learning from delayed rewards. Ph.D. dissertation, Kings’s Collenge, London, May 1989. ID - ref7 ER - TY - STD TI - Watkins CJCH, Dayan P. Q-learning, Machine Learning, vol. 8, no. 3, pp. 279–292, May 1992. https://doi.org/10.1007/BF00992698. UR - https://doi.org/10.1007/BF00992698 ID - ref8 ER - TY - STD TI - Mnih V, Kavukcuoglu K, Silver D, Graves A, Antonoglou I, Wierstra D, Riedmiller MA. Playing atari with deep reinforcement learning, CoRR, vol. abs/1312.5602, 2013. [Online]. Available: http://arxiv.org/abs/1312.5602. UR - http://arxiv.org/abs/1312.5602 ID - ref9 ER - TY - STD TI - Mnih V, Badia AP, Mirza M, Graves A, Lillicrap T, Harley T, Silver D, Kavukcuoglu K. Asynchronous methods for deep reinforcement learning, In: Proceedings of The 33rd International Conference on Machine Learning, ser. In: Proceedings of Machine Learning Research, Balcan MF, Weinberger KQ, (eds), vol. 48. New York, New York, USA: PMLR, 20–22 Jun 2016, pp. 1928–1937. http://proceedings.mlr.press/v48/mniha16.html. UR - http://proceedings.mlr.press/v48/mniha16.html ID - ref10 ER -