| Energy transport in a concentrated suspension of bacteria T Ishikawa, N Yoshida, H Ueno, M Wiedeman, Y Imai, T Yamaguchi Physical review letters 107 (2), 028102, 2011 | 97 | 2011 |
| Production of character animation in a home robot: A case study of lovot N Yoshida, S Yonemura, M Emoto, K Kawai, N Numaguchi, H Nakazato, ... International Journal of Social Robotics 14 (1), 39-54, 2022 | 36 | 2022 |
| Reinforcement learning with state-dependent discount factor N Yoshida, E Uchibe, K Doya 2013 IEEE third joint international conference on development and learning …, 2013 | 32 | 2013 |
| Homeostatic agent for general environment N Yoshida Journal of Artificial General Intelligence 8 (1), 1-22, 2017 | 23 | 2017 |
| Embodiment perspective of reward definition for behavioural homeostasis N Yoshida, T Daikoku, Y Nagai, Y Kuniyoshi Deep RL Workshop NeurIPS 2021, 2021 | 15 | 2021 |
| On reward function for survival N Yoshida arXiv preprint arXiv:1606.05767, 2016 | 8 | 2016 |
| Emergence of integrated behaviors through direct optimization for homeostasis N Yoshida, T Daikoku, Y Nagai, Y Kuniyoshi Neural Networks 177, 106379, 2024 | 6 | 2024 |
| Q-networks for binary vector actions N Yoshida arXiv preprint arXiv:1512.01332, 2015 | 4 | 2015 |
| Homeostatic reinforcement learning through soft behavior switching with internal body state N Yoshida, H Kanazawa, Y Kuniyoshi 2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023 | 3 | 2023 |
| From retina to behavior: prey-predator recognition by convolutional neural networks and their modulation by classical conditioning N Yoshida Adaptive Behavior 24 (4), 195-218, 2016 | 2 | 2016 |
| Homeostatic reinforcement learning explains foraging strategies E Arikawa, N Yoshida, H Kanazawa, Y Kuniyoshi 11th International Symposium on Adaptive Motion of Animals and Machines …, 2023 | 1 | 2023 |
| Unexpected Capability of Homeostasis for Open-ended Learning N Yoshida, Y Kuniyoshi OSF, 2025 | | 2025 |
| Modeling long-term nutritional behaviors using deep homeostatic reinforcement learning N Yoshida, E Arikawa, H Kanazawa, Y Kuniyoshi PNAS nexus 3 (12), pgae540, 2024 | | 2024 |
| Emergence of Implicit World Models from Mortal Agents K Horibe, N Yoshida arXiv preprint arXiv:2411.12304, 2024 | | 2024 |
| Empathic Coupling of Homeostatic States for Intrinsic Prosociality N Yoshida, K Man arXiv preprint arXiv:2412.12103, 2024 | | 2024 |
| Synthesising integrated robot behaviour through reinforcement learning for homeostasis N Yoshida, H Kanazawa, Y Kuniyoshi bioRxiv, 2024.06. 03.597087, 2024 | | 2024 |
| The Architecture of a Multilayer Perceptron for Actor-Critic Algorithm with Energy-based Policy N Yoshida | | 2015 |
| A104 せん断流れ中のツリガネムシの振る舞い (A1-1 生体計測 1) 吉田尚人， 菊地謙次， 鹿毛あずさ， 沼山恵子， 永井萌土， 石川拓司 バイオフロンティア講演会講演論文集 2015.26, 7-8, 2015 | | 2015 |
Yasuo KuniyoshiSchool of Information Science and Technology, The University of TokyoEmail verificata su isi.imi.i.u-tokyo.ac.jp