참고문헌 (34)

1. M. Tonkin, J. Vitale, S. Herse, M.-A. Williams, W. Judge, and X. Wang, "Design Methodology for the UX of HRI: A Field Study of a Commercial Social Robot at an Airport," 2018 ACM/IEEE International Conference on Human-Robot Interaction, Chicago IL, USA, pp. 407-415, 2018, DOI: 10.1145/3171221.3171270. 

   

2. T. Morita, N. Kashiwagi, A. Yorozu, H. Suzuki, and T. Yamaguchi, "Evaluation of a multi-robot cafe based on service quality dimensions," The Review of Socionetwork Strategies, vol. 14, no.1, pp. 55-76, 2020, DOI: 10.1007/s12626-019-00049-x. 

   상세보기

3. R. A. Knepper, T. Layton, J. Romanishin, and D. Rus, "IkeaBot: An autonomous multi-robot coordinated furniture assembly system," 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, DOI: 10.1109/ICRA.2013.6630673. 

   

4. J. Kober, J. A. Bagnell, and J. Peters, "Reinforcement learning in robotics: A survey," The International Journal of Robotics Research, vol. 32, no. 11, 2013, DOI: 10.1177/0278364913495721. 

   상세보기

5. H. Nguyen and H. La, "Review of deep reinforcement learning for robot manipulation," 2019 Third IEEE International Conference on Robotic Computing (IRC), Naples, Italy, pp. 590-595, 2019, DOI: 10.1109/IRC.2019.00120. 

   

6. A. L. Thomaz, G. Hoffman, and C. Breazeal, "Reinforcement learning with human teachers: Understanding how people want to teach robots," ROMAN 2006-The 15th IEEE International Symposium on Robot and Human Interactive Communication, Hatfield, UK, 2006, DOI: 10.1109/ROMAN.2006.314459. 

   

7. V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller, "Playing atari with deep reinforcement learning," arXiv preprint arXiv:1312.5602, 2013, DOI: 10.48550/arXiv.1312.5602. 

   

8. Y. Kim and B.-Y. Kang, "Cooperative robot for table balancing using q-learning," The Journal of Korea Robotics Society, vol. 15, no. 4, pp. 404-412, Dec., 2020, DOI: 10.7746/jkros.2020.15.4.404. 

   원문보기 상세보기

9. B. Price and C. Boutilier, "Accelerating reinforcement learning through implicit imitation," Journal of Artificial Intelligence Research, vol. 19, pp. 569-629, 2003, DOI: 10.1613/jair.898. 

   상세보기

10. Z. Wang and M. E. Taylor, "Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human/Agent's Demonstration," arXiv preprint arXiv:1805.04493, 2018, DOI: 10.48550/arXiv.1805.04493. 

    

11. T. Brys, A. Harutyunyan, H. B. Suay, S. Chernova, M. E. Taylor, and A. Nowe, "Reinforcement learning from demonstration through shaping," 24th International Conference on Artificial Intelligence, pp. 3352-3358, 2015, [Online], https://dl.acm.org/doi/abs/10.5555/2832581.2832716. 

12. M. Ullerstam and M. Mizukawa, "Teaching robots behavior patterns by using reinforcement learning: how to raise pet robots with a remote control," SICE 2004 Annual Conference, Sapporo, Japan, 2004, [Online], https://ieeexplore.ieee.org/document/1491384. 

13. W. B. Knox and P. Stone, "Interactively shaping agents via human reinforcement: The TAMER framework," Fifth International Conference on Knowledge Capture, pp. 9-16, 2009, DOI: 10.1145/1597735.1597738. 

    

14. S. Griffith, K. Subramanian, J. Scholz, C. L. Isbell, and A. L. Thomaz, "Policy shaping: Integrating human feedback with reinforcement learning," Advances in neural information processing systems 26 (NIPS 2013), 2013, [Online], https://proceedings.neurips.cc/paper/2013/hash/e034fb6b66aacc1d48f445ddfb08da98-Abstract.html. 

15. T. A. Kessler Faulkner, E. S. Short, and A. L. Thomaz, "Interactive reinforcement learning with inaccurate feedback," 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, DOI: 10.1109/ICRA40945.2020.9197219. 

    

16. V. Veeriah, P. M. Pilarski, and R. S. Sutton, ''Face valuing: Training user interfaces with facial expressions and reinforcement learning,'' arXiv:1606.02807, 2016, [Online], http://arxiv.org/abs/1606.02807. 

17. R. Arakawa, S. Kobayashi, Y. Unno, Y. Tsuboi, and S. Maeda, Dqn-tamer: Human-in-the-loop reinforcement learning with intractable feedback," arXiv preprint arXiv:1810.11748, 2018, [Online], https://arxiv.org/abs/1810.11748. 

18. NAO the humanoid and programmable robot | SoftBank Robotics, [Online], https://www.softbankrobotics.com/emea/en/nao, Access: Jun. 7, 2022. 

19. H.-S. Lee and B.-Y. Kang, "Continuous emotion estimation of facial expressions on JAFFE and CK+ datasets for human-robot interaction," Intelligent Service Robotics, vol. 13, no.1, 2020, DOI: 10.1007/s11370-019-00301-x. 

    상세보기

20. M. Lyons, M. Kamachi, M., and J. Gyoba, "The Japanese Female Facial Expression (JAFFE) Dataset," Third International Conference on Automatic Face and Gesture Recognition, Apr., 1998, DOI: 10.5281/zenodo.3451524. 

    

21. P. Lucey, J. F. Cohn, T. Kanade, J. Saragih, Z. Ambadar, and I. Matthews, "The extended cohn-kanade dataset (CK+): A complete dataset for action unit and emotion-specified expression," 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, San Francisco, CA, USA, 2010, DOI: 10.1109/CVPRW.2010.5543262. 

    

22. J. A. Russel, "A circumplex model of affect," Journal of Personality and Social Psychology, vol. 39, no. 6, pp. 1161-1178, 1980, DOI: 10.1037/h0077714. 

    상세보기

23. P. Shakyawar, P. Choure, and U. Singh, "Eigenface method through facial expression recognition," 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), Coimbatore, India, 2017, DOI: 10.1109/ICECA.2017.8212714. 

    

24. H. Zou and L. Xue, "A selective overview of sparse principal component analysis," Proceedings of the IEEE, vol. 106, no. 8, pp. 1311-1320, Aug., 2018, DOI: 10.1109/JPROC.2018.2846588. 

    상세보기

25. R. Ewing and K. Park, "Linear regression," Basic Quantitative Research Methods for Urban Planners. Routledge, pp. 220-269, 2020, [Online], https://books.google.co.kr/books?hlko&%lr&idGzz3DwAAQBAJ&oifnd&pgPP1&otsHJz-Tw6pgs&sigoFD_mUSrG3iw3pFr8_uL9bc0STw&redi%r_escy#vonepage&q&ffalse. 

26. V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, S. Petersen, C. Beattie, A. Sadik, I. Antonoglou, H. King, D. Kumaran, D. Wierstra, S. Legg, and D. Hassabis, "Human-level control through deep reinforcement learning," Nature, vol. 518, no. 7540, pp. 529-533 2015, DOI: 10.1038/nature14236. 

    상세보기

27. T.-T. Wong, "Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation," Pattern Recognition vol. 48, no. 9, pp. 2839-2846, May, 2015, DOI: 10.1016/j.patcog.2015.03.009. 

    상세보기

28. H. Jeon, Y. Kim, and B.-Y. Kang, "Interactive Reinforcement Learning for Table Balancing Robot," Second International Combined Workshop on Spatial Language Understanding and Grounded Communication for Robotics, 2021, DOI: 10.18653/v1/2021.splurobonlp-1.8. 

    

29. T. Schaul, I. Antonoglou, and D. Silver, "Unit Tests for Stochastic Optimization," arXiv Preprint arXiv:1312.6055, 2013, DOI: 10.48550/arXiv.1312.6055. 

    

30. D. P. Kingma and J. Ba, "Adam: A Method for Stochastic Optimization," arXiv preprint arXiv:1412. 6980, 2014, DOI: 10.48550/arXiv.1412.6980. 

    

31. J. Duchi, E. Hazan, and Y. Singer, "Adaptive Subgradient Methods for Online Learning and Stochastic Optimization," Journal of Machine Learning Research, vol. 12, pp. 2121-2159, 2011, [Online], https://www.jmlr.org/papers/volume12/duchi11a/duchi11a.pdf. 

    상세보기

32. M. D. Zeiler, "ADADELTA: An Adaptive Learning Rate Method," arXiv Preprint arXiv:1212.5701, 2012, DOI: 10.48550/arXiv.1212.5701. 

    

33. E. M. Dogo, O. J. Afolabi, N. I. Nwulu, B. Twala, and C. O. Aigbavboa, "A Comparative Analysis of Gradient Descent-Based Optimization Algorithms on Convolutional Neural Networks," 2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS), Belgaum, India, 2018, DOI: 10.1109/CTEMS.2018.8769211. 

    

34. I. Kandel, M. Castelli, and A. Popovic, "Comparative study of first order optimizers for image classification using convolutional neural networks on histopathology images," Journal of Imaging, vol. 6, no. 9, 2020, DOI: 10.3390/jimaging6090092. 

    상세보기

저자의 다른 논문 :

강보영 (11)