E. Uchibe

Henrik I. Christensen, Kenji Doya, Stefan Elfwing, 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

Strategy Classification in Multi-agent Environment — Applying Reinforcement Learning to Soccer Agents —

Minoru Asada, Koh Hosoda, Eiji Uchibe, 2004 .

State Space Construction for Cooperative Behavior Acquisition in the Environments Including Multiple Learning Robots

Minoru Asada, Eiji Uchibe, Koh Hosoda, 2002 .

Cooperative behavior acquisition in multi-mobile robots environment by reinforcement learning based on state vector estimation

Minoru Asada, Koh Hosoda, Eiji Uchibe, 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

Vision Based State Space Construction for Learning Mobile Robots in Multi-agent Environments

Minoru Asada, Koh Hosoda, Eiji Uchibe, 1997, EWLR.

Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning

Junichiro Yoshimoto, Jan Peters, Kenji Doya, 2010, Neural Computation.

Deep learning, reinforcement learning, and world models

Yann LeCun, Doina Precup, M. Sahani, 2022, Neural Networks.

A Vision-Based Reinforcement Learning For Coordination Of Soccer Playing Behaviors

Minoru Asada, Shoichi Noda, Eiji Uchibe, 2004 .

Expected energy-based restricted Boltzmann machine for classification

Kenji Doya, Stefan Elfwing, Eiji Uchibe, 2015, Neural Networks.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task

Kenji Doya, Eiji Uchibe, Ken Kinjo, 2013, Front. Neurorobot..

Deep reinforcement learning with smooth policy update: Application to robotic cloth manipulation

Takamitsu Matsubara, Yoshihisa Tsurumine, Yunduan Cui, 2019, Robotics Auton. Syst..

Model-Free Deep Inverse Reinforcement Learning by Logistic Regression

Eiji Uchibe, E. Uchibe, 2018, Neural Processing Letters.

Darwinian embodied evolution of the learning ability for survival

Henrik I. Christensen, Kenji Doya, Stefan Elfwing, 2011, Adapt. Behav..

Co-evolution for cooperative behavior acquisition in a multiple mobile robot environment

Minoru Asada, Eiji Uchibe, Masateru Nakamura, 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

Cooperative and Competitive Reinforcement and Imitation Learning for a Mixture of Heterogeneous Learning Modules

Eiji Uchibe, E. Uchibe, 2018, Front. Neurorobot..

Constrained Deep Q-Learning Gradually Approaching Ordinary Q-Learning

Shin Ishii, Yuji Yasui, Eiji Uchibe, 2019, Front. Neurorobot..

Reinforcement Learning with Multiple Heterogeneous Modules: A Framework for Developmental Robot Learning

E. Uchibe, K. Doya, K. Doya, 2005, Proceedings. The 4nd International Conference on Development and Learning, 2005..

Model-Free Deep Inverse Reinforcement Learning by Logistic Regression

E. Uchibe, 2018, Neural Processing Letters.

Modular deep reinforcement learning from reward and punishment for robot navigation

Stefan Elfwing, Eiji Uchibe, Jiexin Wang, 2020, Neural Networks.

Theoretical Analysis of Efficiency and Robustness of Softmax and Gap-Increasing Operators in Reinforcement Learning

Kenji Doya, Eiji Uchibe, Tadashi Kozuno, 2019, AISTATS.

Competitive-Cooperative-Concurrent Reinforcement Learning with Importance Sampling

K. Doya, E. Uchibe, 2004 .

Reinforcement learning-based optimal control of unknown constrained-input nonlinear systems using simulated experience

E. Uchibe, H. J. Asl, 2023, Nonlinear Dynamics.

Reinforcement learning with state-dependent discount factor

Naoto Yoshida, Kenji Doya, Eiji Uchibe, 2013, 2013 IEEE Third Joint International Conference on Development and Learning and Epigenetic Robotics (ICDL).

Evolutionary Development of Hierarchical Learning Structures

Henrik I. Christensen, Kenji Doya, Stefan Elfwing, 2007, IEEE Transactions on Evolutionary Computation.

An Evolutionary Approach to Automatic Construction of the Structure in Hierarchical Reinforcement Learning

Kenji Doya, Stefan Elfwing, Eiji Uchibe, 2003, GECCO.

Efficient sample reuse in policy search by multiple importance sampling

Eiji Uchibe, E. Uchibe, 2018, GECCO.

Adaptive Baseline Enhances EM-Based Policy Search: Validation in a View-Based Positioning Task of a Smartphone Balancer

Kenji Doya, Jiexin Wang, Eiji Uchibe, 2017, Front. Neurorobot..

Robustness of linearly solvable Markov games employing inaccurate dynamics model

Kenji Doya, Eiji Uchibe, Ken Kinjo, 2018, Artificial Life and Robotics.

Incremental Coevolution With Competitive and Cooperative Tasks in a Multirobot Environment

Minoru Asada, Eiji Uchibe, M. Asada, 2006, Proceedings of the IEEE.