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ORCIDEiji Uchibe
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2020 – today
- 2024
[j35]Hamed Jabbari Asl
, Eiji Uchibe:
Estimating cost function of expert players in differential games: A model-based method and its data-driven extension. Expert Syst. Appl. 255: 124687 (2024)- [j34]Hamed Jabbari Asl, Eiji Uchibe:
Online estimation of objective function for continuous-time deterministic systems. Neural Networks 172: 106116 (2024) - [j33]Hamed Jabbari Asl, Eiji Uchibe:
Inverse reinforcement learning methods for linear differential games. Syst. Control. Lett. 193: 105936 (2024) - [c37]Jiexin Wang, Eiji Uchibe:
Reward-Punishment Reinforcement Learning with Maximum Entropy. IJCNN 2024: 1-7 - [i11]Jiexin Wang, Eiji Uchibe:
Reward-Punishment Reinforcement Learning with Maximum Entropy. CoRR abs/2405.11784 (2024) - [i10]Satoshi Yagi, Mitsunori Tada, Eiji Uchibe, Suguru Kanoga, Takamitsu Matsubara, Jun Morimoto:
Unsupervised Neural Motion Retargeting for Humanoid Teleoperation. CoRR abs/2406.00727 (2024) - 2023
- [j32]Hamed Jabbari Asl, Eiji Uchibe:
Online Reinforcement Learning Control of Nonlinear Dynamic Systems: A State-action Value Function Based Solution. Neurocomputing 544: 126291 (2023) - 2022
- [j31]Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto:
Deep learning, reinforcement learning, and world models. Neural Networks 152: 267-275 (2022) - [j30]Tomoya Yamanokuchi, Yuhwan Kwon, Yoshihisa Tsurumine, Eiji Uchibe, Jun Morimoto, Takamitsu Matsubara:
Randomized-to-Canonical Model Predictive Control for Real-World Visual Robotic Manipulation. IEEE Robotics Autom. Lett. 7(4): 8964-8971 (2022) - [j29]Eiji Uchibe:
Model-Based Imitation Learning Using Entropy Regularization of Model and Policy. IEEE Robotics Autom. Lett. 7(4): 10922-10929 (2022) - [c36]Hamed Jabbari Asl, Eiji Uchibe:
Online Data-Driven Inverse Reinforcement Learning for Deterministic Systems. SSCI 2022: 884-889 - [i9]Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara:
q-Munchausen Reinforcement Learning. CoRR abs/2205.07467 (2022) - [i8]Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara:
Enforcing KL Regularization in General Tsallis Entropy Reinforcement Learning via Advantage Learning. CoRR abs/2205.07885 (2022) - [i7]Eiji Uchibe:
Model-Based Imitation Learning Using Entropy Regularization of Model and Policy. CoRR abs/2206.10101 (2022) - [i6]Tomoya Yamanokuchi, Yuhwan Kwon, Yoshihisa Tsurumine, Eiji Uchibe, Jun Morimoto, Takamitsu Matsubara:
Randomized-to-Canonical Model Predictive Control for Real-world Visual Robotic Manipulation. CoRR abs/2207.01840 (2022) - 2021
- [j28]Jiexin Wang, Stefan Elfwing, Eiji Uchibe:
Modular deep reinforcement learning from reward and punishment for robot navigation. Neural Networks 135: 115-126 (2021) - [j27]Eiji Uchibe, Kenji Doya:
Forward and inverse reinforcement learning sharing network weights and hyperparameters. Neural Networks 144: 138-153 (2021) - [j26]Tom Macpherson, Masayuki Matsumoto, Hiroaki Gomi, Jun Morimoto, Eiji Uchibe, Takatoshi Hikida:
Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control. Neural Networks 144: 507-521 (2021) - 2020
- [i5]Eiji Uchibe, Kenji Doya:
Imitation learning based on entropy-regularized forward and inverse reinforcement learning. CoRR abs/2008.07284 (2020)
2010 – 2019
- 2019
- [j25]Shota Ohnishi, Eiji Uchibe, Yotaro Yamaguchi, Kosuke Nakanishi, Yuji Yasui, Shin Ishii:
Constrained Deep Q-Learning Gradually Approaching Ordinary Q-Learning. Frontiers Neurorobotics 13: 103 (2019) - [j24]Yoshihisa Tsurumine, Yunduan Cui, Eiji Uchibe, Takamitsu Matsubara:
Deep reinforcement learning with smooth policy update: Application to robotic cloth manipulation. Robotics Auton. Syst. 112: 72-83 (2019) - [c35]Tadashi Kozuno, Eiji Uchibe, Kenji Doya:
Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning. AISTATS 2019: 2995-3003 - 2018
- [j23]Ken Kinjo, Eiji Uchibe, Kenji Doya:
Robustness of linearly solvable Markov games employing inaccurate dynamics model. Artif. Life Robotics 23(1): 1-9 (2018) - [j22]Eiji Uchibe:
Cooperative and Competitive Reinforcement and Imitation Learning for a Mixture of Heterogeneous Learning Modules. Frontiers Neurorobotics 12: 61 (2018) - [j21]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning. Neural Networks 107: 3-11 (2018) - [j20]Eiji Uchibe:
Model-Free Deep Inverse Reinforcement Learning by Logistic Regression. Neural Process. Lett. 47(3): 891-905 (2018) - [c34]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Online meta-learning by parallel algorithm competition. GECCO 2018: 426-433 - [c33]Eiji Uchibe:
Efficient sample reuse in policy search by multiple importance sampling. GECCO 2018: 545-552 - [c32]Jiexin Wang, Stefan Elfwing, Eiji Uchibe:
Deep Reinforcement Learning by Parallelizing Reward and Punishment using the MaxPain Architecture. ICDL-EPIROB 2018: 175-180 - [i4]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Unbounded Output Networks for Classification. CoRR abs/1807.09443 (2018) - 2017
- [j19]Jiexin Wang, Eiji Uchibe, Kenji Doya:
Adaptive Baseline Enhances EM-Based Policy Search: Validation in a View-Based Positioning Task of a Smartphone Balancer. Frontiers Neurorobotics 11: 1 (2017) - [c31]Chris Reinke, Eiji Uchibe, Kenji Doya:
Average Reward Optimization with Multiple Discounting Reinforcement Learners. ICONIP (1) 2017: 789-800 - [c30]Yoshihisa Tsurumine, Yunduan Cui, Eiji Uchibe, Takamitsu Matsubara:
Deep dynamic policy programming for robot control with raw images. IROS 2017: 1545-1550 - [i3]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning. CoRR abs/1702.03118 (2017) - [i2]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Online Meta-learning by Parallel Algorithm Competition. CoRR abs/1702.07490 (2017) - [i1]Tadashi Kozuno, Eiji Uchibe, Kenji Doya:
Unifying Value Iteration, Advantage Learning, and Dynamic Policy Programming. CoRR abs/1710.10866 (2017) - 2016
- [j18]Jiexin Wang, Eiji Uchibe, Kenji Doya:
EM-based policy hyper parameter exploration: application to standing and balancing of a two-wheeled smartphone robot. Artif. Life Robotics 21(1): 125-131 (2016) - [j17]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
From free energy to expected energy: Improving energy-based value function approximation in reinforcement learning. Neural Networks 84: 17-27 (2016) - [c29]Qiong Huang, Eiji Uchibe, Kenji Doya:
Emergence of communication among reinforcement learning agents under coordination environment. ICDL-EPIROB 2016: 57-58 - [c28]Eiji Uchibe:
Deep Inverse Reinforcement Learning by Logistic Regression. ICONIP (1) 2016: 23-31 - 2015
- [j16]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Expected energy-based restricted Boltzmann machine for classification. Neural Networks 64: 29-38 (2015) - 2014
- [c27]Eiji Uchibe, Kenji Doya:
Inverse reinforcement learning using Dynamic Policy Programming. ICDL-EPIROB 2014: 222-228 - [c26]Eiji Uchibe, Kenji Doya:
Combining learned controllers to achieve new goals based on linearly solvable MDPs. ICRA 2014: 5252-5259 - 2013
- [j15]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Scaled free-energy based reinforcement learning for robust and efficient learning in high-dimensional state spaces. Frontiers Neurorobotics 7: 3 (2013) - [j14]Ken Kinjo, Eiji Uchibe, Kenji Doya:
Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task. Frontiers Neurorobotics 7: 7 (2013) - [c25]Naoto Yoshida, Eiji Uchibe, Kenji Doya:
Reinforcement learning with state-dependent discount factor. ICDL-EPIROB 2013: 1-6 - 2011
- [j13]Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen:
Darwinian embodied evolution of the learning ability for survival. Adapt. Behav. 19(2): 101-120 (2011) - 2010
- [j12]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Jan Peters, Kenji Doya:
Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning. Neural Comput. 22(2): 342-376 (2010) - [c24]Stefan Elfwing, Makoto Otsuka, Eiji Uchibe, Kenji Doya:
Free-Energy Based Reinforcement Learning for Vision-Based Navigation with High-Dimensional Sensory Inputs. ICONIP (1) 2010: 215-222
2000 – 2009
- 2009
- [c23]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Emergence of Different Mating Strategies in Artificial Embodied Evolution. ICONIP (2) 2009: 638-647 - [c22]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya:
A Generalized Natural Actor-Critic Algorithm. NIPS 2009: 1312-1320 - [p1]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
Co-evolution of Rewards and Meta-parameters in Embodied Evolution. Creating Brain-Like Intelligence 2009: 278-302 - 2008
- [j11]Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen:
Co-evolution of Shaping Rewards and Meta-Parameters in Reinforcement Learning. Adapt. Behav. 16(6): 400-412 (2008) - [j10]Takashi Sato, Eiji Uchibe, Kenji Doya:
Learning how, what, and whether to communicate: emergence of protocommunication in reinforcement learning agents. Artif. Life Robotics 12(1-2): 70-74 (2008) - [j9]Tetsuro Morimura, Eiji Uchibe, Kenji Doya:
Natural actor-critic with baseline adjustment for variance reduction. Artif. Life Robotics 13(1): 275-279 (2008) - [j8]Eiji Uchibe, Kenji Doya:
Finding intrinsic rewards by embodied evolution and constrained reinforcement learning. Neural Networks 21(10): 1447-1455 (2008) - [c21]Takumi Kamioka, Eiji Uchibe, Kenji Doya:
NeuroEvolution Based on Reusable and Hierarchical Modular Representation. ICONIP (1) 2008: 22-31 - [c20]Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto, Kenji Doya:
A New Natural Policy Gradient by Stationary Distribution Metric. ECML/PKDD (2) 2008: 82-97 - 2007
- [j7]Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen:
Evolutionary Development of Hierarchical Learning Structures. IEEE Trans. Evol. Comput. 11(2): 249-264 (2007) - [c19]Eiji Uchibe, Kenji Doya:
Finding Exploratory Rewards by Embodied Evolution and Constrained Reinforcement Learning in the Cyber Rodents. ICONIP (2) 2007: 167-176 - 2006
- [j6]Eiji Uchibe, Minoru Asada:
Incremental Coevolution With Competitive and Cooperative Tasks in a Multirobot Environment. Proc. IEEE 94(7): 1412-1424 (2006) - 2005
- [j5]Kenji Doya, Eiji Uchibe:
The Cyber Rodent Project: Exploration of Adaptive Mechanisms for Self-Preservation and Self-Reproduction. Adapt. Behav. 13(2): 149-160 (2005) - [c18]Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen:
Biologically inspired embodied evolution of survival. Congress on Evolutionary Computation 2005: 2210-2216 - 2004
- [c17]Stefan Elfwing, Eiji Uchibe, Kenji Doya, Henrik I. Christensen:
Multi-agent reinforcement learning: using macro actions to learn a mating task. IROS 2004: 3164-3169 - 2003
- [c16]Stefan Elfwing, Eiji Uchibe, Kenji Doya:
An Evolutionary Approach to Automatic Construction of the Structure in Hierarchical Reinforcement Learning. GECCO 2003: 507-509 - 2002
- [j4]Eiji Uchibe, Masakazu Yanase, Minoru Asada:
Behavior generation for a mobile robot based on the adaptive fitness function. Robotics Auton. Syst. 40(2-3): 69-77 (2002) - 2001
- [j3]Minoru Asada, Eiji Uchibe:
Multiagent Learning towards RoboCup. New Gener. Comput. 19(2): 103-120 (2001) - [c15]Eiji Uchibe, Tatsunori Kato, Koh Hosoda, Minoru Asada:
Dynamic Task Assignment in a Multiagent/Multitask Environment based on Module Conflict Resolution. ICRA 2001: 3987-3992 - [c14]Eiji Uchibe, Masakazu Yanase, Minoru Asada:
Evolutionary Behavior Selection with Activation/Termination Constraints. RoboCup 2001: 234-243 - 2000
- [c13]Yasutake Takahashi, Eiji Uchibe, Takahashi Tamura, Masakazu Yanase, Shoichi Ikenoue, Shujiro Inui, Minoru Asada:
Osaka University "Trackies 2000". RoboCup 2000: 607-610
1990 – 1999
- 1999
- [j2]Minoru Asada, Eiji Uchibe, Koh Hosoda:
Cooperative Behavior Acquisition for Mobile Robots in Dynamically Changing Real Worlds Via Vision-Based Reinforcement Learning and Development. Artif. Intell. 110(2): 275-292 (1999) - [c12]Eiji Uchibe, Minoru Asada:
Multiple Reward Criterion for Cooperative Behavior Acquisition in a Muliagent Environment. RoboCup 1999: 519-530 - [c11]Sho'ji Suzuki, Tatsunori Kato, Hiroshi Ishizuka, Hiroyoshi Kawanishi, Takashi Tamura, Masakazu Yanase, Yasutake Takahashi, Eiji Uchibe, Minoru Asada:
The Team Description of Osaka University "Trackies-99". RoboCup 1999: 750-753 - 1998
- [j1]Minoru Asada, Sho'ji Suzuki, Yasutake Takahashi, Eiji Uchibe, Masateru Nakamura, Chizuko Mishima, Hiroshi Ishizuka, Tatsunori Kato:
TRACKIES: RoboCup-97 Middle-Size League World Cochampion. AI Mag. 19(3): 71-78 (1998) - [c10]Eiji Uchibe, Minoru Asada, Koh Hosoda:
State Space Construction for Behavior Acquisition in Multi Agent Environments with Vision and Action. ICCV 1998: 870-875 - [c9]Eiji Uchibe, Minoru Asada, Koh Hosoda:
Cooperative Behavior Acquisition in Multi Mobile Robots Environment by Reinforcement Learning Based on State Vector Estimation. ICRA 1998: 1558-1563 - [c8]Eiji Uchibe, Minoru Asada, Koh Hosoda:
Environmental Complexity Control for Vision-Based Learning Mobile Robot. ICRA 1998: 1865-1870 - [c7]Eiji Uchibe, Masateru Nakamura, Minoru Asada:
Co-evolution for cooperative behavior acquisition in a multiple mobile robot environment. IROS 1998: 425-430 - [c6]Eiji Uchibe, Masateru Nakamura, Minoru Asada:
Cooperative Behavior Acquisition in a Multiple Mobile Robot Environment by Co-evolution. RoboCup 1998: 273-285 - [c5]Sho'ji Suzuki, Tatsunori Kato, Hiroshi Ishizuka, Yasutake Takahashi, Eiji Uchibe, Minoru Asada:
An Application of Vision-Based Learning in RoboCup for a Real Robot with an Omnidirectional Vision System and the Team Description of Osaka University "Trackies". RoboCup 1998: 316-325 - 1997
- [c4]Eiji Uchibe, Minoru Asada, Koh Hosoda:
Vision Based State Space Construction for Learning Mobile Robots in Multi-agent Environments. EWLR 1997: 62-78 - [c3]Sho'ji Suzuki, Yasutake Takahashi, Eiji Uchibe, Masateru Nakamura, Chizuko Mishima, Hiroshi Ishizuka, Tatsunori Kato, Minoru Asada:
Vision-Based Robot Learning Towards RoboCup: Osaka University "Trackies". RoboCup 1997: 305-319 - 1996
- [c2]Eiji Uchibe, Minoru Asada, Koh Hosoda:
Behavior coordination for a mobile robot using modular reinforcement learning. IROS 1996: 1329-1336 - 1994
- [c1]Minoru Asada, Eiji Uchibe, Shoichi Noda, Sukoya Tawaratsumida, Koh Hosoda:
Coordination of multiple behaviors acquired by a vision-based reinforcement learning. IROS 1994: 917-924
Coauthor Index
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last updated on 2024-12-10 20:51 CET by the dblp team
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