Journal papers

  • Kang, S., Ishihara, K., Sugimoto, N., Morimoto, J. (2023/11).
    Curriculum-based humanoid robot identification using large-scale human motion database
    Front. Robot. AI, Vol.10
  • Chiyohara, S., Furukawa, J., Noda, T., Morimoto, J., Imamizu, H. (2023/11).
    Proprioceptive short‑term memory in passive motor learning
    Scientific Reports, Vol.13 (1), 20826
  • 細井 雄一郎、紙本 貴之、野田 智之、河口 大洋、寺前 達也、山田 祐歌、辻 哲也、川上 途行 (2023/10).
    臨床神経生理学, Vol.51 (5), pp.576
  • Kamimoto, T., Hosoi, Y., Tanamachi, K., Yamamoto, R., Yamada, Y., Teramae, T., Noda, T., Kaneko, F., Tsuji, T., Kawakami, M. (2023/08).
    Combined Ankle Robot Training and Robot-assisted Gait Training Improved the Gait Pattern of a Patient with Chronic Traumatic Brain Injury
    Prog. Rehabil. Med., Vol.8
  • Jabbari Asl, H., Uchibe, E. (2023/08).
    Online Reinforcement Learning Control of Nonlinear Dynamic Systems: A State-action Value Function Based Solution
    Neurocomputing, Vol.544, 126291
  • Takai, A., Teramae, T., Noda, T., Ishihara, K., Furukawa, J., Fujimoto, H., Hatakenaka, M., Fujita, N., Jino, A., Hiramatsu, Y., Miyai, I., Morimoto, J. (2023/07).
    Development of split-force-controlled body weight support (SF-BWS) robot for gait rehabilitation
    Front. Hum. Neurosci., Vol.17, 1197380
  • Jabbari Asl, H., Uchibe, E. (2023/07).
    Reinforcement learning-based optimal control of unknown constrained-input nonlinear systems using simulated experience
    Nonlinear Dynamics, Vol.111 (17), pp.16093–16110
  • 森 公彦、桑原 嵩幸、脇田 正徳、間野 直人、久保 峰鳴、中條 雄太、寺前 達也、野田 智之、長谷 公隆 (2023/05).
    Jpn. J. Rehabil. Med., Vol.60 (Suppl.)
  • 桑原 嵩幸、森 公彦、久保 峰鳴、間野 直人、中條 雄太、寺前 達也、野田 智之、長谷 公隆 (2023/05).
    Jpn. J. Rehabil. Med., Vol.60 (Suppl.)
  • 新明 俊英、瀧口 述弘、藤島 弘樹、平野 佑典、寺前 達也、野田 智之 (2023/05).
    Jpn. J. Rehabil. Med., Vol.60 (Suppl.)
  • Takahashi, Y., Okada, K., Noda, T., Teramae, T., Nakamura, T., Haruyama, K., Okuyama, K., Tsujimoto, K., Mizuno, K., Morimoto, J., Kawakami, M. (2023/01).
    Robotized Knee-Ankle-Foot Orthosis-Assisted Gait Training on Genu Recurvatum during Gait in Patients with Chronic Stroke: A Feasibility Study and Case Report
    Journal of clinical medicine, Vol.12 (2)
  • 間野 直人、中條 雄太、森 公彦、桑原 嵩幸、久保 峰鳴、寺前 達也、野田 智之、長谷 公隆 (2022/10).
    臨床神経生理学, Vol.50 (5), pp.461
  • 久保 峰鳴、間野 直人、桑原 嵩幸、中條 雄太、森 公彦、森 拓也、寺前 達也、野田 智之、長谷 公隆 (2022/10).
    臨床神経生理学, Vol.50 (5), pp.395
  • Yamanokuchi, T., Kwon, Y., Tsurumine, Y., Uchibe, E., Morimoto, J., Matsubara, T. (2022/10).
    Randomized-to-Canonical Model Predictive Control for Real-World Visual Robotic Manipulation
    IEEE Robotics and Automation Letters, Vol..7 (4), pp. 8964-8971
  • Uchibe, E. (2022/10).
    Model-Based Imitation Learning Using Entropy Regularization of Model and Policy
    IEEE Robotics and Automation Letters, Vol..7 (4), pp. 8964-8971
  • Matsuo, Y., LeCun, Y., Sahani, M., Precup, D., Silver, D., Sugiyama, M., Uchibe, E., Morimoto, J. (2022/08).
    Deep learning, reinforcement learning, and world models
    Neural Networks, Vol.152, pp.267-275
  • 桑原 嵩幸、森 公彦、久保 峰鳴、間野 直人、中條 雄太、野田 智之、長谷 公隆 (2022/05).
    Jpn. J. Rehabil. Med., Vol.59 (特別号), S589
  • Zhu, L., Chen, Z., Uchibe, E., Matsubara, T. (2022/05).
    Enforcing KL Regularization in General Tsallis Entropy Reinforcement Learning via Advantage Learning
    Comput. Res. Repos. (CoRR), arXiv:2205.07885
  • 春山 幸志郎、川上 途行、野田 智之、中村 拓也、都築 圭太、奥山 航平、寺前 達也、岡田 紘佑、森本 淳、藤原 俊之 (2021/12).
    慢性期脳卒中者に対する膝-足関節ロボット歩行介入が歩行能力に及ぼす効果 : 単一症例における検討
    理学療法学Supplement, Vol.48 (suppl-1), pp.168
  • Furukawa, J., Chiyohara, S., Teramae, T., Takai, A., Morimoto, J. (2021/10).
    A Collaborative Filtering Approach Toward Plug-and-Play Myoelectric Robot Control
    IEEE Transactions on Human-Machine Systems, Vol.51 (5), pp.514-523
  • 藤田 暢一、藤本 宏明、平松 佑一、高井 飛鳥、寺前 達也、古川 淳一朗、畠中 めぐみ、神尾 昭宏、野田 智之、森本 淳、宮井 一郎 (2021/03).
    理学療法学Supplement, Vol.47 (suppl-1), pp.127
  • 野田 智之,Yuta CHUJO (2022/04).
    How to decide the number of gait cycles in different low-pass filters to extract motor modules by non-negative matrix factorization during walking in chronic post-stroke patients
    Frontiers in Human Neuroscience April 2022/ Vol.16, Article 803542
  • Furukawa, J., Okajima, S., An, Q., Nakamura, Y., Morimoto, J. (2022/02).
    Selective Assist Strategy by Using Lightweight Carbon Frame Exoskeleton Robot
    Vol.7/ No.2/pp.3890-3897 10.1109/LRA.2022.3148799
  • Takeshi D. Itoh,Koji Ishihara,Jun Morimoto (2022/01).
    Implicit Contact Dynamics Modeling With Explicit Inertia Matrix Representation for Real-Time, Model-Based Control in Physical Environment
    Neural Computation (2022) 34 (2): 360–377.
  • Takai,A., Fu,Q., Doibata,Y., Lisi, G.,Tsuchiya, T., Mojtahedi,K., Yoshioka,T., Kawato M., Morimoto, J., Santello, M. (2021/12).
    Leaders are made: Learning acquisition of consistent leader-follower relationships depends on implicit haptic interactions.
  • Takai,A., Lisi, G., Noda, T., Teramae, T., Imamizu, H., Morimoto,J. (2021/10).
    Bayesian Estimation of Potential Performance Improvement Elicited by Robot-Guided Training
    Frontiers in Neuroscience Vol.15,No.704402
  • 石原弘二、 森本淳 (2021/09).
    日本ロボット学会誌 39巻 7号 p. 597-600
  • Macpherson, T., Matsumoto, M., Gomi, H., Morimoto,J., Uchibe,E., Hidaka, T. (2021/09).
    Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control
    Neural Networks Vol.144, pp.507-521
  • Furukawa,J., Chiyohara,S., Teramae,T., Takai,A., Morimoto,J. (2021/08).
    A collaborative filtering approach toward plug-and-play myoelectric robot control
    IEEE Transactions on Human-Machine Systems
  • Furukawa,J., Morimoto,J.(2021/01).
    Composing an assistive control strategy based on linear bellman combination from estimated user’s motor goal
    IEEE Robotics and Automation Letters Vol.6,No.2,pp.1051-1058
  • Teramae,T., Matsubara,T., Noda,T., Morimoto,J.(2020/10).
    Quaternion-based trajectory optimization of human postures for inducing target
    IEEE Robotics and Automation Letters Vol.5, No.4, pp.6607-6614
  • Uchibe,E., Doya,K.(2020/08).
    Imitation learning based on entropy-regularized forward and inverse reinforcement learning
  • Pahic,R., Ridge,B., Gams,A., Morimoto,J., Ude,A.(2020/04).
    Training of deep neural networks for the generation of dynamic movement primitives
    Neural Netowrks Vol.127, pp.121-131
  • Ohnishi,S., Uchibe,E., Yamaguchi,Y., Nakanishi,K., Yasui,Y., Ishii,S. (2019/12).
    Constrained deep Q-learning gradually approaching ordinary Q-learning
    Frontiers in Neurorobotics Vol.13, Article 103
  • Ishihara,K., Itoh D.T., Morimoto,J. (2019/10).
    Full-body optimal control toward versatile and agile behaviors in a humanoid robot
    “IEEE Robotics and Automation Letters Vol.5,No.1,pp.119-126”
  • Iwane,F., Lisi,G., Morimoti,J. (2019/08).
    EEG sensorimotor correlates of speed during forearm passive movements
    IEEE Transactions on Neural Systems and Rehabilitation Engineering Vol.27,Issue9, pp.1667-1675
  • Hamaya,M., Matsubara,T., Teramae,T., Noda,T., Morimoto,J. (2019/06).
    Design of physical user-robot interactions for model identification of soft
    International Journal of Robotics Research
  • Ugurlu B., Forni,P., Doppmann,C., Sariyiliz,E., Morimoto,J. (2019/05).
    Stable control of force, position, and stiffness for robot joints powered via pneumatic muscles
    IEEE Transactions on Industrial Informatics
  • Petric,T., Peternel,L., Morimoto,J., Babic,J. (2019/05).
    Assistive arm-exoskeleton control based on human muscular manipulability
    Frontiers in Neurorobotics Vol.13, Article 30
  • Tsurumine, Y.,Cui,Y., Uchibe,E., Matsubara,T. (2018/11).
    Deep reinforcement learning with smooth policy update: application to robotic cloth manipulation
    Robotics and Autonomous Systems Vol.112, pp.72-83
  • Teramae,T., Ishihara, K., Babic,J., Morimoto,J. Oztop,E. (2018/11).
    Human-in-the-loop control and task learning for pneumatically actuated muscle based robots
    Frontiers in Human-in-the-Loop Robot Control and Learning                  Vol.12, Article 71
  • Uchibe,E. (2018/09).
    Cooperative and competitive reinforcement and imitation learning for a mixture of heterogeneous learning modules
    Frontiers in Neurorobotics Vol.12,Artcle61
  • Ewerton,M., Rother, D., Weimar, O.J., Kollegger,G., Wiemeyer J., Peters, J., Maeda,G (2018/05).
    Assisting movement training and execution with visual and haptic feedback
    Frontiers in Robotics and AI Vol.24, Article 24, pp.1-19
  • Lisi,G., Rivela,D., Takai,A., Morimoto,J. (2018/02).
    Markov switching model for quick detection of event related desynchronization in EEG
    Frontiers in Neuroscience-Neuroprosthetics Vol.12, Article 24
  • Ishihara,K., Morimoto,J. (2018/01).
    An optimal control strategy for hybrid actuator systems: application to an artificial muscle with electric motor assist
    Neural Networks Vol.99, pp.92-100
  • Gasper,T., Nemec,B., Morimoto,J., Ude,A. (2017/12).
    Skill learning and action recognition by arc-length dynamic movement primitives
    Robotics and Autonomous Systems Vol.100, pp.225-235
  • Hamaya,M., Tatsubara,T., Noda,T., Teramae,T., Morimoto,J. (2017/11).
    Learning assistive strategies for exoskeleton robots from user-robot physical interaction
    Pattern Recognition Letters Vol.99, pp.67-76
  • Kozono,T., Uchibe,E., Doya,K. (2017/10).
    Unifying value iteration, advantage learning, and dynamic policy programming arXiv:1710.10866
  • Kinjo,K., Uchibe,E., Doya,K. (2017/10).
    Robustness of linearly solvable markov games employing inaccurate dynamics model
    Journal of Artificial Life and Robotics Vol.23,Issue1, pp.1-9
  • Teramae,T., Noda,T., Morimoto,J. (2017/08).
    EMG-based model predictive control for physical human-robot interaction: Application for assist-as-needed control
    IEEE Robotics and Automation Letters(RA-L) Vol.3, No.1, pp.210-217
  • Ichikawa,N., Lisi,G., Yahata,N., Okada,G., Takamura,M., Yamada,M., Suhara,T., Hashimoto,R., Yamada,T., Yoshihara,Y., Takahashi,H., Kasai,K., Kato,N., Yamawaki,S., Kawato,M., Morimoto,J., Okamoto,Y. (2017/04).
    Identifying melancholic depression biomarker using whole-brain functional connectivity arXiv:1704.01039
  • Furukawa,J., Noda,T., Teramae,T., Morimoto,J. (2017/04).
    Human movement modeling to detect biosignal sensor failures for myoelectric assistive robot control
    IEEE Transactions on Robotics Vol.33, No.4, pp.846-856
  • Wang,J., Uchibe,E., Doya,K. (2017/01).
    Adaptive baseline enhances EM-based policy search: validation in a view-based positioning task of a smartphone balancer
    Frontiers in Neurorobotics(Web) Vol.11, Article 1
  • Elfwing,S., Uchibe,E., Doya,K. (2016/08).
    From free energy to expected energy:improving energy-based value function approximation in reinforcement learning
    Neural Networks Vol.84,pp.17-27
  • 内部英治 (2016/03).
    日本神経回路学会誌 Vol.23, No.1, pp.2-13
  • Sugimoto,N., Tangkaratta,V., Wensveen,T., Zhao,T., Sugiyama,M., Morimoto,J. (2016/02).
    Trial and error: using previous experiences as simulation models in humanoid motor learning
    IEEE Robotics and Automation Magazine Vol.23, Issue 1, pp.96-105
  • Peternel,L., Noda,T., Petric,T., Ude,A., Morimoto,J., Babic,J. (2016/02).
    Adaptive control of exoskeleton robots for periodic assistive behaviours based on EMG feedback minimisation
    PLoS ONE Vol.11, Issue2, e0148942
  • Gams,A., Petric,T., Do,M., Nemec,B., Morimoto,J., Asfour,T., Ude,A. (2016/01).
    Adaptation and coaching of periodic motion primitives through physical and visual interaction
    Robotics and Autonomous Systems Vol.75, Part B, pp.340-351
  • Ugurlu,B., Doppmann,C., Hamaya,M., Forni,P., Teramae,T., Noda,T., Morimoto,J. (2015/06).
    Variable ankle stiffness improves balance control:experiments on a bipedal exoskeleton
    IEEE Transactions on Mechatronics Vol.21,No.1,pp.79-87
  • Tangkaratt, V., Mori, S., Zhao, T., Mmorimoto, J., Sugiyama, M. (2015).
    Model-based policy gradients with parameter-based exploration by least-squares conditional density estimation
    Neural Networks, Vol.57, 128-140
  • Morimoto, J., Kawato, M. (2015).
    Creating the brain and interacting with the brain:an Integrated approach to understanding the brain
    Journal of the Royal Society Interface, Vol.12, 104, 20141250
  • Furukawa, J., Noda, T., Teramae, T., Morimoto, J. (2015).
    Fault tolerant approach for biosignal-based robot control
    Advanced Robotics, Vol.29, 7, 505-514.
  • Lisi, G., Morimoto, J. (2015).
    EEG single-trial detection of gait speed changes treadmill walk
    PLoS ONE, Vol.10, 4, 1-28.
  • Bouyarmane, K., Vaillant, J., Sugimoto, N., Keith, F., Furukawa, J., Morimoto, J. (2014).
    Brain-machine interfacing control of whole-body humanoid motion
    Frontiers in Systems Neurosciences, Vol.8, 138, 1-10.
  • Lisi, G., Noda, T., Morimoto, J. (2014).
    Decoding the ERD/ERS: influence of afferent input induced by a leg assistive robot
    Frontiers in Neuroscience, Vol.8, 85, 1-12.
  • Furukawa, J., Noda, T., Teramae, T., Morimoto, J. (2014).
    An EMG-driven weight support system with pneumatic artificial muscles
    IEEE Systems Journal, DOI:10.1109/JSYST.2014.2330376.
  • Ugurlu, B., Saglia, J., Tsagarakis, N., Morfey, S., Caldwell, D. (2014).
    Bipedal hopping pattern generation for passively compliant humanoids:exploiting the resonance
    IEEE Transactions on Industrial Electronics, Vol.61, 10, 5431-5443.
  • 森本淳, 杉本徳和 (2013).
    計測と制御, Vol.52, 8, 742-748.
  • Zhao, T., Hachiya, H., Tangkaratt, V., Morimoto, J., Sugiyama, M. (2013).
    Efficient sample reuse in policy gradients with parameter-based exploration
    Neural Computation, Vol.25, 6, 1512-1547.
  • Ariki, Y., Hyon, S., Morimoto, J. (2013).
    Extraction of primitive representation from captured human movements and measured ground reaction force to generate physically consistent imitated behaviors
    Neural Networks, Vol.40, 32-43.
  • Matsubara, T., Morimoto, J. (2013).
    Bilinear modeling of EMG Signals to extract user-independent features for multiuser myoelectric interface
    IEEE Transactions on Biomedical Engineering, Vol.60, 8, 2205-2213.
  • 松原崇充, 森本淳 (2013).
    電子情報通信学会論文誌D, Vol.J96-D, 2, 298-305.
  • Schiebener, D., Morimoto, J., Asfour, T., Ude, A. (2013).
    Integrating visual perception and manipulation for autonomous learning of object representations
    Adaptive Behavior, Vol.21, 5, 328-345.
  • Manoonpong, P., Kolodziejski, C., Worgotter, F., Morimoto, J. (2013).
    Combining correlation-based and reward-based learning in neural control for policy improvement
    Advances in Complex Systems, Vol.16, 2&3, 1350015-pp.1-38.
  • Forte, D., Gams, A., Morimoto, J., Ude, A. (2012).
    On-line motion synthesis and adaptation using a trajectory database
    Robotics and Autonomous Systems, Vol.60, 10, 1327-1339.
  • 内方章雅, 松原崇充, 森本淳 (2012).
    電子情報通信学会和文論文誌D, J95-D, 7, 1476-1487.
  • Sugimoto, N., Haruno, M., Doya, K., Kawato, M. (2012).
    Mosaic for multiple-reward environments.
    Neural Computation, 24, 3, 577-606.
  • Matsubara, T., Hyon, S., Morimoto, J. (2012).
    Real-time stylistic prediction for whole-body human motions.
    Neural Networks, 25, 191-199.
  • Matsubara, T., Hyon, S., Morimoto, J. (2011).
    Learning parametric dynamic movement primitives from multiple demonstrations.
    Neural Networks, 24, Issue 5, 493-500.
  • 松原崇充, 玄相昊, 森本淳 (2011).
    電子情報通信学会論文誌, J94-D, 1, 344-355.
  • Ude, A., Gams, A., Asfour, T., Morimoto, J. (2010).
    Task-specific generalization of discrete and periodic dynamic movement primitives.
    IEEE Transactions on Robotics, 26, 5, 800-815.
  • 玄相昊, 里宇明元 (2010).
    バイオメカニズム学会誌, 34, 1, 5-11.
  • 玄相昊 (2009).
    日本ロボット学会誌, 27, 9, 1025-1028.
  • Hyon, S. (2009).
    A motor control strategy with virtual musculoskeletal systems for compliant anthropomorphic robots.
    IEEE/ASME Transactions on Mechatronics, 14, 6, 677-688.
  • Morimoto, J., Atkeson, C. G. (2009).
    Nonparametric representation of an approximated poincare map for learning biped locomotion.
    Autonomous Robots, Vol.27, 2, 131-144.
  • 玄相昊 (2009).
    日本ロボット学会誌, 27, 2, 178-187.
  • Hyon, S. (2009).
    Compliant terrain adaptation for biped humanoids without measuring ground surface and contact forces.
    IEEE Transactions on Robotics, 25, 1, 171-178.
  • Ude, A., Omrcen, D., Cheng, G. (2008).
    Making object learning and recognition an active process.
    International Journal of Humanoid Robotics, 5, 2, 267-286.
  • Hale, J. G., Hohl, B., Hyon, S., Matsubara, T., Moraud, E. M., Cheng, G. (2008).
    Highly precise dynamic simulation environment for humanoid robots.
    Advanced Robotics: Special Issue on Humanoid Technologies and Systems, 22, 10, 1075-1105.
  • Matsubara, T., Morimoto, J., Nakanishi, J., Hyon, S., Hale, J. G., Cheng, G. (2008).
    Learning to acquire whole-body humanoid center of mass movements to achieve dynamic tasks.
    Advanced Robotics: Special Issue on Humanoid Technologies and Systems, 22, 10, 1125-1142.
  • Nakanishi, J., Cory, R., Mistry, M., Peters, J., Schaal, S. (2008).
    Operational Space Control: A theoretical and empirical comparison.
    International Journal of Robotics Research, 27, 6, 737-757.
  • 玄相昊, 藤本健治 (2008).
    日本ロボット学会誌, 26, 4, 372-380.
  • Moren, J., Ude, A., Koene, A., Cheng, G. (2008).
    Biologically based top-down attention modulation for humanoid interactions.
    International Journal of Humanoid Robotics, 5, 1, 3-24.
  • Endo, G., Morimoto, J., Matsubara, T., Nakanishi, J., Cheng, G. (2008).
    Learning CPG-based biped locomotion with a policy gradient method: Application to a humanoid robot.
    The International Journal of Robotics Research, Special Issue on Machine Learning in Robotics, 27, 2, 213-228.
  • Chaminade, T., Oztop, E., Cheng, G., Kawato, M. (2008).
    From self-observation to imitation: Visuomotor association on a robotic hand.
    Brain Research Bulletin, 75, 775-784.
  • Morimoto, J., Endo, G., Nakanishi, J., Cheng, G. (2008).
    A biologically inspired biped locomotion strategy for humanoid robots: Modulation of simple sinusoidal patterns by a coupled oscillator model.
    IEEE Transaction on Robotics, 24, 1, 185-191.
  • Cheng, G., Metta, G., Cannata, G., Sandini, G. (2008).
    Humanoid technologies:”Know-how”.
    Robotics and Autonomous Systems, 56, Issue 1, 1-3.
  • 佐藤訓志, 藤本健治, 玄相昊 (2007).
    計測自動制御学会論文集, 3, 12, 1103-1110.
  • Peters, J., Mistry, M., Udwadia, F., Nakanishi, J., Schaal, S. (2007).
    A unifying framework for robot control with redundant DOFs.
    Autonomous Robots, Vil.24, 1, 1-12.
  • Hyon, S., Hale, J. G., Cheng, G. (2007).
    Full-body compliant human-humanoid interaction: Balancing in the presence of unknown external forces.
    IEEE Transactions on Robotics, 23, 5, 884-898.
  • Koene, A., Arnold, D., Johnston, A. (2007).
    Bimodal sensory discrimination is finer than dual single modality discrimination.
    Journal of Vision, 7, 11, Article14, 1-11.
  • Cheng, G., Hyon, S., Morimoto, J., Ude, A., Hale, J. G., Colvin, G., Scroggin, W., Jacobsen, S. C. (2007).
    CB: A humanoid research platform for exploring neuroscience.
    Journal of Advance Robotics, 21, 10, 1097-1114.
  • Ude, A., Moren, J., Cheng, G. (2007).
    Visual attention and distributed processing of visual information for the control of humanoid robots.
    Humanoid Robots Human-like Machines (International Journal of Advanced Robotic Systems), 423-436.
  • Morimoto, J., Atkeson, C. (2007).
    Learning biped locomotion: Application of poincare-map-based reinforcement learning.
    IEEE Robotics and Automation Magazine, 14, 2, 41-51.
  • Koene, A. R., Zhaoping, L. (2007).
    Feature-specific interactions in salience from combined feature contrasts: Evidence for a bottom-up saliency map in V1.
    Journal of Vision, 7, 7, Article 6, 1-14.
  • Morimoto, J., Doya, K. (2007).
    Reinforcement learning state estimator.
    Neural Computation, 19, 3, 730-756.
  • Oztop, E. (2006).
    An upper bound on the minimum number of onomials required to separate dichotomies of {-1,1}n.
    Neural Computation, 18, 3119-3138.
  • Matsubara, T., Morimoto, J., Nakanishi, J., Sato, M., Doya, K. (2006).
    Learning CPG-based biped locomotion with a policy gradient method.
    Robotics and Autonomous Systems, 54,911-920.
  • 中西淳, Schaal, S. (2006).
    神経回路学会誌 2006年3月号 受賞概要, 13, 1, 37-38.
  • Oztop, E., Imamizu, H., Cheng, G., Kawato, M. (2006).
    A computational model of anterior intraparietal (AIP) neurons.
    Neurocomputing, 69, 1354-1361.
  • Oztop, E., Kawato, M., Arbib, M. A. (2006).
    Mirror neurons and limitation: A computationally guided review.
    Neural Networks, 19 254-271.
  • Oztop, E., Franklin, D. W., Chaminade, T., Cheng, G. (2005).
    Human-humanoid interaction: Is a humanoid robot perceived as a human?.
    International Journal of Humanoid Robotics, 2, 4, 537-559.
  • Cheng, G., Schaal, S., Atkeson, C. G. (2005).
    Editorial by guest editor.
    International Journal of Humanoid Robotics, 2, 4, Editorial 389-390.
  • Hale, J. G. (2005).
    Practical and theoretical research into humanoid motion and interaction.
    IEEE System, Man, and Cybernetics Society eNewsletter / Internet News Letter.
  • Hale, J. G., Pollick, F. E. (2005).
    ‘Sticky hands’: Learning and generalisation for cooperative physical interactions with a humanoid robot.
    IEEE Transactions on Systems, Man, and Cybernetics : Part C, 35, 4, 512-521.
  • Arbib, M. A., Oztop, E., Zukow-goldring, P. (2005).
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