K. Doya

Yasuharu Koike, Kenji Doya, K. Doya, 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

Meta-learning in Reinforcement Learning

Kenji Doya, Nicolas Schweighofer, K. Doya, 2003, Neural Networks.

Multiple Model-Based Reinforcement Learning

Mitsuo Kawato, Kenji Doya, Kazuyuki Samejima, 2002, Neural Computation.

Consensus Paper: Towards a Systems-Level View of Cerebellar Function: the Interplay Between Cerebellum, Basal Ganglia, and Cortex

Andreea C. Bostan, K. Doya, J. Houk, 2016, The Cerebellum.

Bifurcations in the learning of recurrent neural networks

K. Doya, K. Doya, 1992, [Proceedings] 1992 IEEE International Symposium on Circuits and Systems.

Electrophysiological properties of inferior olive neurons: A compartmental model.

K. Doya, M. Kawato, N. Schweighofer, 1999, Journal of neurophysiology.

Metalearning and neuromodulation

Kenji Doya, K. Doya, 2002, Neural Networks.

Validation of Decision-Making Models and Analysis of Decision Variables in the Rat Basal Ganglia

K. Doya, Makoto Ito, 2009, The Journal of Neuroscience.

Representation of Action-Specific Reward Values in the Striatum

K. Doya, M. Kimura, K. Samejima, 2005, Science.

Chaos may enhance information transmission in the inferior olive.

K. Doya, M. Kawato, N. Schweighofer, 2004, Proceedings of the National Academy of Sciences of the United States of America.

Unsupervised learning of granule cell sparse codes enhances cerebellar adaptive control

K. Doya, N. Schweighofer, F. Lay, 2001, Neuroscience.

A Hodgkin-Huxley Type Neuron Model That Learns Slow Non-Spike Oscillations

Kenji Doya, Allen I. Selverston, Peter F. Rowat, 1993, NIPS.

A hierarchical Bayesian method to resolve an inverse problem of MEG contaminated with eye movement artifacts

Masa-aki Sato, Mitsuo Kawato, Kenji Doya, 2009, NeuroImage.

Anterior and superior lateral occipito-temporal cortex responsible for target motion prediction during overt and covert visual pursuit

K. Doya, M. Kawato, T. Shibata, 2006, Neuroscience Research.

Selection of Neural Architecture and the Environment Complexity

K. Doya, E. Uchibe, G. Capi, 2002 .

Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops

Saori C. Tanaka, K. Doya, Y. Okamoto, 2004, Nature Neuroscience.

Serotonin and the Evaluation of Future Rewards

Saori C. Tanaka, K. Doya, N. Schweighofer, 2007, Annals of the New York Academy of Sciences.

What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?

Kenji Doya, K. Doya, 1999, Neural Networks.

Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional data

Junichiro Yoshimoto, Kenji Doya, Kosuke Yoshida, 2017, BMC Bioinformatics.

A Neural Correlate of Reward-Based Behavioral Learning in Caudate Nucleus: A Functional Magnetic Resonance Imaging Study of a Stochastic Decision Task

K. Doya, M. Kawato, M. Haruno, 2004, The Journal of Neuroscience.

Switching particle filters for efficient real-time visual tracking

Shin Ishii, Kenji Doya, Takashi Bando, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

The Cyber Rodent Project: Exploration of Adaptive Mechanisms for Self-Preservation and Self-Reproduction

Kenji Doya, Eiji Uchibe, K. Doya, 2005, Adapt. Behav..

Emergence of Different Mating Strategies in Artificial Embodied Evolution

Kenji Doya, Stefan Elfwing, Eiji Uchibe, 2009, ICONIP.

Average Reward Optimization with Multiple Discounting Reinforcement Learners

Kenji Doya, Eiji Uchibe, Chris Reinke, 2017, ICONIP.

Serotonin Differentially Regulates Short- and Long-Term Prediction of Rewards in the Ventral and Dorsal Striatum

Saori C. Tanaka, K. Doya, N. Schweighofer, 2007, PloS one.

An excellent year and a transition

DeLiang Wang, John G. Taylor, Kenji Doya, 2011, Neural Networks.

Analysis of Structure-Function Relationship Using a Whole-Brain Dynamic Model Based on MRI Images of the Common Marmoset

Shin Ishii, Ken Nakae, Kenji Doya, 2018 .

Switching particle filters for efficient visual tracking

Shin Ishii, Kenji Doya, Takashi Bando, 2006, Robotics Auton. Syst..

Hierarchical Bayesian estimation for MEG inverse problem

Masa-aki Sato, Mitsuo Kawato, Kenji Doya, 2004, NeuroImage.

Estimating Internal Variables and Paramters of a Learning Agent by a Particle Filter

Kenji Doya, Minoru Kimura, Kazuyuki Samejima, 2003, NIPS.

Neural Information Processing

Akira Hirose, Minho Lee, Derong Liu, 2016, Lecture Notes in Computer Science.

Toward Probabilistic Diagnosis and Understanding of Depression Based on Functional MRI Data Analysis with Logistic Group LASSO

Kenji Doya, Junichiro Yoshimoto, Yasumasa Okamoto, 2015, PloS one.

Model-based analysis of decision variables

Makoto Ito, Kenji Doya, Kazuyuki Samejima, 2011 .

Reinforcement learning with multiple representations in the basal ganglia loops for sequential motor control

Kenji Doya, Hiroyuki Nakahara, Okihide Hikosaka, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Emergence of Hierarchy via Reinforcement Learning Using a Multiple Timescale Stochastic RNN pdf

Dongqi Han, Kenji Doya, Jun Tani, 2019, ArXiv.

Neural substrate of dynamic Bayesian inference in the cerebral cortex

K. Doya, B. Kuhn, A. Funamizu, 2016, Nature Neuroscience.

Hierarchical Chunking during Learning of Visuomotor Sequences

Ahmed, Kenji Doya, Raju S. Bapi, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Self-consistent neuronal population under spike inputs and unbalanced conditions

Kenji Doya, Carlos E. Gutierrez, Junichiro Yoshimoto, 2015, 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS).

Evolution of meta-parameters in reinforcement learning algorithm

Kenji Doya, Genci Capi, Anders Eriksson, 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

Inter-module credit assignment in modular reinforcement learning

Mitsuo Kawato, Kenji Doya, Kazuyuki Samejima, 2003, Neural Networks.

Connectivity inference from neural recording data: Challenges, mathematical bases and research directions

Junichiro Yoshimoto, Kenji Doya, Ildefons Magrans de Abril, 2017, Neural Networks.

Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning

Kenji Doya, Stefan Elfwing, Eiji Uchibe, 2017, Neural Networks.

Universality of Fully-Connected Recurrent Neural Networks

Kenji Doya, K. Doya, 1993 .

Optimization and validation of diffusion MRI-based fiber tracking with neural tracer data as a reference

Shin Ishii, Ken Nakae, Kenji Doya, 2019, Scientific reports.

A Model of the Electrophysiological Properties of the Inferior Olive Neurons

Mitsuo Kawato, Kenji Doya, Nicolas Schweighofer, 1998, ICONIP.

Optogenetic Activation of Dorsal Raphe Serotonin Neurons Enhances Patience for Future Rewards

Kenji F. Tanaka, K. Doya, A. Yamanaka, 2014, Current Biology.

Activation of Dorsal Raphe Serotonin Neurons Is Necessary for Waiting for Delayed Rewards

K. Doya, K. Miyazaki, K. Miyazaki, 2012, The Journal of Neuroscience.

Creating Brain-Like Intelligence: From Basic Principles to Complex Intelligent Systems

Bernhard Sendhoff, Olaf Sporns, Kenji Doya, 2009, Creating Brain-Like Intelligence.

Model-based Empowerment Computation for Dynamical Agents

Kenji Doya, Takashi Ikegami, Yuma Kajihara, 2019, 2019 IEEE Symposium Series on Computational Intelligence (SSCI).

Constrained reinforcement learning from intrinsic and extrinsic rewards

E. Uchibe, K. Doya, K. Doya, 2007, 2007 IEEE 6th International Conference on Development and Learning.

The Role of Serotonin in the Regulation of Patience and Impulsivity

K. Doya, K. Miyazaki, K. Miyazaki, 2012, Molecular Neurobiology.

Low-Serotonin Levels Increase Delayed Reward Discounting in Humans

Saori C. Tanaka, K. Doya, N. Schweighofer, 2008, The Journal of Neuroscience.

Biologically inspired embodied evolution of survival

Henrik I. Christensen, Kenji Doya, Stefan Elfwing, 2005, 2005 IEEE Congress on Evolutionary Computation.

Scaled free-energy based reinforcement learning for robust and efficient learning in high-dimensional state spaces

Kenji Doya, Stefan Elfwing, Eiji Uchibe, 2013, Front. Neurorobot..

Promoting Further Developments of Neural Networks

DeLiang Wang, Kenji Doya, K. Doya, 2017, Neural Networks.

Exciting Time for Neural Networks

K. Doya, Deliang Wang, 2015 .

A computational neural model of goal-directed utterance selection

Günther Palm, Kenji Doya, Hans Kamp, 2010, Neural Networks.

Neural Information Processing

Akira Hirose, Minho Lee, Derong Liu, 2016, Lecture Notes in Computer Science.

Neural Information Processing

Akira Hirose, Minho Lee, Derong Liu, 2016, Lecture Notes in Computer Science.

Finding intrinsic rewards by embodied evolution and constrained reinforcement learning

Kenji Doya, Eiji Uchibe, K. Doya, 2008, Neural Networks.

Different Cortico-Basal Ganglia Loops Specialize in Reward Prediction at Different Time Scales

Kenji Doya, Kazutaka Ueda, Yasumasa Okamoto, 2003, NIPS.

Changing the structure of complex visuo-motor sequences selectively activates the fronto-parietal network

Ahmed, Kenji Doya, Raju S. Bapi, 2012, NeuroImage.

Memorizing oscillatory patterns in the analog neuron network

K. Doya, S. Yoshizawa, K. Doya, 1989, International 1989 Joint Conference on Neural Networks.

Calcium Responses Model in Striatum Dependent on Timed Input Sources

Junichiro Yoshimoto, Kenji Doya, Jeffery R. Wickens, 2009, ICANN.

Resting state functional connectivity explains individual scores of multiple clinical measures for major depression

Junichiro Yoshimoto, Kenji Doya, Kosuke Yoshida, 2015, 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Bayesian System Identification of Molecular Cascades

Junichiro Yoshimoto, Kenji Doya, K. Doya, 2007, ICONIP.

Cerebellar aminergic neuromodulation: towards a functional understanding

K. Doya, N. Schweighofer, Shinya Kuroda, 2004, Brain Research Reviews.

Multiple Representations of Belief States and Action Values in Corticobasal Ganglia Loops

K. Doya, K. Samejima, 2007, Annals of the New York Academy of Sciences.

3 3 A Computational Model of Avian Song Learning

T. Sejnowski, K. Doya, 2000 .

Modulators of decision making

K. Doya, 2008, Nature Neuroscience.

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

Kenji Doya, Junichiro Yoshimoto, Yasumasa Okamoto, 2015, PloS one.

Benefit of Multiple Representations for Motor Sequence Control in The Basal Ganglia Loops

Kenji Doya, Hiroyuki Nakahara, Okihide Hikosaka, 1998 .

Dimension Reduction of Biological Neuron Models by Artificial Neural Networks

Kenji Doya, Allen I. Selverston, K. Doya, 1994, Neural Computation.

Self-developed Action Hierarchy Enhances Meta Reinforcement Learning.

K. Doya, J. Tani, Dongqi Han, 2019 .

Uncertainty in action-value estimation affects both action choice and learning rate of the choice behaviors of rats

K. Doya, R. Kanzaki, Makoto Ito, 2012, The European journal of neuroscience.

A biologically constrained spiking neural network model of the primate basal ganglia with overlapping pathways exhibits action selection

K. Doya, B. Girard, B. Delord, 2020, The European journal of neuroscience.

Reinforcement learning: Computational theory and biological mechanisms

K. Doya, 2007, HFSP journal.

Understanding Neural Coding through the Model-Based Analysis of Decision Making

K. Doya, G. Corrado, 2007, The Journal of Neuroscience.

Inter-individual discount factor differences in reward prediction are topographically associated with caudate activation

Saori C. Tanaka, K. Doya, N. Schweighofer, 2011, Experimental Brain Research.

Hierarchical Reinforcement Learning for Multiple Reward Functions

K. Doya, E. Uchibe, 2004 .

Reinforcement learning: Computational theory and biological mechanisms

K. Doya, 2007 .

Multiple representations and algorithms for reinforcement learning in the cortico-basal ganglia circuit

K. Doya, Makoto Ito, 2011, Current Opinion in Neurobiology.

Current trends in decision making.

K. Doya, B. Balleine, J. O'Doherty, 2007, Annals of the New York Academy of Sciences.

Reward-Predictive Neural Activities in Striatal Striosome Compartments

K. Doya, Makoto Ito, Tomohiko Yoshizawa, 2018, eNeuro.

The Basal Ganglia, Reinforcement Learning, and the Encoding of Value

K. Doya, M. Kimura, 2014 .

Selecting Optimal Behaviors Based on Contexts

K. Doya, D. Wolpert, M. Kawato, 2003 .

Serotonin Affects Association of Aversive Outcomes to Past Actions

Saori C. Tanaka, K. Doya, N. Schweighofer, 2009, The Journal of Neuroscience.

Distinct Neural Representation in the Dorsolateral, Dorsomedial, and Ventral Parts of the Striatum during Fixed- and Free-Choice Tasks

K. Doya, Makoto Ito, 2015, The Journal of Neuroscience.

Reward Responses on the Multiple T Task Sequential Navigation: Separation of Spatial and Neuronal Activity in the Rodent Dorsal Striatum in

Mackenzie W. Mathis, K. Doya, A. Redish, 2015 .

Derivation of integrated state equation for combined outputs-inputs vector of discrete-time linear time-invariant system and its application to reinforcement learning

K. Doya, E. Uchibe, H. Anai, 2017, 2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

A Spiking Neural Network Model of Model-Free Reinforcement Learning with High-Dimensional Sensory Input and Perceptual Ambiguity

Kenji Doya, Takashi Nakano, Junichiro Yoshimoto, 2015, PloS one.

Near-Saddle-Node Bifurcation Behavior as Dynamics in Working Memory for Goal-Directed Behavior

Kenji Doya, Hiroyuki Nakahara, K. Doya, 1998, Neural Computation.

PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos pdf

Carl E. Rasmussen, Jan Peters, Kenji Doya, 2019, ICML.

Reward probability and timing uncertainty alter the effect of dorsal raphe serotonin neurons on patience

Kenji Doya, Katsuhiko Miyazaki, Akihiro Yamanaka, 2018, Nature Communications.

Activation of the central serotonergic system in response to delayed but not omitted rewards

K. Doya, K. Miyazaki, K. Miyazaki, 2011, The European journal of neuroscience.

Neuroethics Questions to Guide Ethical Research in the International Brain Initiatives

Anna Devor, Arisa Ema, Kenji Doya, 2018, Neuron.

The Basal Ganglia and the Encoding of Value

K. Doya, M. Kimura, 2009 .

Computation of Driving Pleasure based on Driver's Learning Process Simulation by Reinforcement Learning

Kenji Doya, Eiji Uchibe, Yonosuke Miki, 2013 .

Self-Reproduction The Cyber Rodent Project : Exploration of Adaptive Mechanisms for Self-Preservation and

Kenji Doya, Eiji Uchibe, K. Doya, 2005 .

Adaptation in Dynamic Environments by Learning and Evolution

Kenji Doya, Genci Capi, Masao Yokota, 2004 .

Imitation Learning by Estimating Intention of Demonstrator

Mitsuo Kawato, Norikazu Sugimoto, Kenji Doya, 2003 .

Neural circuits for reinforcement learning and mental simulation

Kenji Doya, K. Doya, 2019, IBRO Reports.

Reinforcement Learning and Computational Neuroscience

Kenji Doya, K. Doya, 2002 .

Announcement of the Neural Networks Best Paper Award

Kenji Doya, DeLiang Wang, K. Doya, 2022, Neural Networks.

Mini-special issue: ICONIP 2007

Masumi Ishikawa, Kenji Doya, K. Doya, 2008, Neural Networks.

Reinforcement Learning using Importance Sampling for Multiple Learning Modules

Kenji Doya, Eiji Uchibe, K. Doya, 2003 .

Introduction for 2002 Special Issue: Computational Models of Neuromodulation

Kenji Doya, Michael E. Hasselmo, Peter Dayan, 2002, Neural Networks.

Reinforcement learning under constraints generated by multiple reward functions

Kenji Doya, Eiji Uchibe, K. Doya, 2006 .

Acquisition of Stand-up Behavior by a 3-link 2-joint Robot using Hierarchical Reinforcement Learning

Jun Morimoto, Kenji Doya, K. Doya, 2001 .

Announcement of the Neural Networks Best Paper Award

DeLiang Wang, Kenji Doya, K. Doya, 2017, Neural Networks.

Molecular and network mechanisms of reinforcement learning

Kenji Doya, K. Doya, 2004 .

Learning and Control

Hidenori Kimura, Mitsuo Kawato, Kenji Doya, 2001 .

New action editors join the journal! Five exciting special issues in the works!

Stephen Grossberg, John G. Taylor, Kenji Doya, 2009, Neural Networks.

Fostering deep learning and beyond

DeLiang Wang, Kenji Doya, K. Doya, 2018, Neural Networks.

Continual growth and a transition

K. Doya, T. Toyoizumi, Deliang Wang, 2022, Neural Networks.

Maintaining the Publication Infrastructure in a Worldwide Pandemic

K. Doya, Deliang Wang, 2021, Neural Networks.

Behavioral Data Analysis by Reinforcement Learning Models

Kenji Doya, Kazuyuki Samejima, K. Doya, 2007 .

Announcement of the Neural Networks Best Paper Award

DeLiang Wang, Kenji Doya, K. Doya, 2017, Neural Networks.

Multi-scale, multi-modal neural modeling and simulation

Shin Ishii, Markus Diesmann, Kenji Doya, 2011, Neural Networks.

S3f2-5 Learning model-based analysis of neuroimaging data(S3-f2: "Advances in Anatomical, Functional, and Computational Brain Imaging",Symposia,Abstract,Meeting Program of EABS & BSJ 2006)

Kenji Doya, K. Doya, 2006 .

Recurrent networks: supervised learning

Kenji Doya, K. Doya, 1998 .

Learning algorithms for modeling human behaviors and identifying molecular cascades

Kenji Doya, K. Doya, 1970 .

State of Neural Networks Is Strong

DeLiang Wang, Kenji Doya, K. Doya, 2016, Neural Networks.

Whole brain Probabilistic Generative Model toward Realizing Cognitive Architecture for Developmental Robots pdf

Takayuki Nagai, Hiroshi Yamakawa, Kenji Doya, 2021, Neural Networks.

Learning of Hierarchical Temporal Sequences in Biological Systems.

Kenji Doya, Chikara Hoshino, K. Doya, 2000 .

Loss of a Co-Editor-in-Chief and friend

DeLiang Wang, Kenji Doya, K. Doya, 2012, Neural Networks.

Serotonergic projections to the orbitofrontal and medial prefrontal cortices differentially modulate waiting for future rewards

Kenji F. Tanaka, K. Doya, A. Yamanaka, 2020, Science Advances.

Robotics and the Brain Sciences

K. Doya, 1999 .

Social impact and governance of AI and neurotechnologies

K. Doya, H. Kitano, M. Sakagami, 2022, Neural Networks.

IEEE Control Systems Magazine

K. Doya, M. Kawato, H. Kimura, 2002 .

The Brain/MINDS Marmoset Connectivity Atlas: exploring bidirectional tracing and tractography in the same stereotaxic space

K. Doya, Shin Ishii, Ken Nakae, 2022, bioRxiv.

Forward and inverse reinforcement learning sharing network weights and hyperparameters

K. Doya, E. Uchibe, 2020, Neural Networks.

Imitation learning based on entropy-regularized forward and inverse reinforcement learning

K. Doya, E. Uchibe, 2020, ArXiv.

Deploying and Optimizing Embodied Simulations of Large-Scale Spiking Neural Networks on HPC Infrastructure

Jochen M. Eppler, F. O. Morin, K. Doya, 2022, Frontiers in Neuroinformatics.

Tutorial : The probabilistic brain

K. Doya, G. Goodhill, A. V. Schaik, 2017 .

TALK FRIDAY 2 . 15 PM Spontaneous activity in the developing brain

K. Doya, B. Balleine, G. Goodhill, 2017 .

Activation of dorsal raphe serotonin neurons is necessary for waiting for delayed rewards

K. Doya, K. Miyazaki, K. Miyazaki, 2011, Neuroscience Research.

Dynamics of Basal Ganglia and Thalamus in Parkinsonian Tremor

K. Doya, J. Yoshimoto, J. Morén, 2019, Springer Series in Cognitive and Neural Systems.

Optogenetic activation of dorsal raphe serotonin neurons induces a brain-wide response in reward network

Kenji F. Tanaka, K. Doya, N. Takata, 2022, bioRxiv.

Self-organization of action hierarchy and compositionality by reinforcement learning with recurrent neural networks

K. Doya, J. Tani, Dongqi Han, 2019, Neural Networks.

V ARIATIONAL O RACLE G UIDING FOR R EINFORCE MENT L EARNING

K. Doya, Xufang Luo, Yuqing Yang, 2022 .

Speaker 2: Yasumasa Okamoto

Saori C. Tanaka, K. Doya, K. Miyazaki, 2016, International Journal of Neuropsychopharmacology.

Neural Networks special issue on Artificial Intelligence and Brain Science

Karl J. Friston, K. Doya, Masashi Sugiyama, 2022, Neural Networks.

Neuronal Representation of a Working Memory-Based Decision Strategy in the Motor and Prefrontal Cortico-Basal Ganglia Loops

K. Doya, Makoto Ito, Tomohiko Yoshizawa, 2022, eNeuro.

Recurrent Networks : Learning Algorithms ∗

Kenji Doya, K. Doya, 2002 .

A Spiking Neural Network Builder for Systematic Data-to-Model Workflow

K. Doya, C. E. Gutierrez, Henrik Skibbe, 2022, Frontiers in Neuroinformatics.

Body and visual instabilities functionally modulate implicit reaching corrections

K. Doya, H. Gomi, Naotoshi Abekawa, 2022, iScience.

Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional data

K. Doya, J. Yoshimoto, Kosuke Yoshida, 2017, BMC Bioinformatics.

A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots

K. Doya, Masahiro Suzuki, T. Nagai, 2021, Neural Networks.

Robust Reinforcement Learning

Jun Morimoto, Kenji Doya, K. Doya, 2005, Neural Computation.

Multi-agent reinforcement learning: using macro actions to learn a mating task

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

Multi-agent reinforcement learning: an approach based on the other agent's internal model

Shin Ishii, Kenji Doya, Yasuo Nagayuki, 2000, Proceedings Fourth International Conference on MultiAgent Systems.

MOSAIC for Multiple-Reward Environments

Mitsuo Kawato, Norikazu Sugimoto, Kenji Doya, 2012, Neural Computation.

Reinforcement Learning State Estimator

Jun Morimoto, Kenji Doya, K. Doya, 2007, Neural Computation.

Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning

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

A model-based prediction of the calcium responses in the striatal synaptic spines depending on the timing of cortical and dopaminergic inputs and post-synaptic spikes

Junichiro Yoshimoto, Kenji Doya, Takashi Nakano, 2013, Front. Comput. Neurosci..

Nitric Oxide Regulates Input Specificity of Long-Term Depression and Context Dependence of Cerebellar Learning

Mitsuo Kawato, Kenji Doya, Hideaki Ogasawara, 2006, PLoS Comput. Biol..

Brain computation mechanism of prediction and decision making by dorsal raphe serotonin neurons.

K. Doya, K. Miyazaki, K. Miyazaki, 2017, Nihon yakurigaku zasshi. Folia pharmacologica Japonica.

Canonical cortical circuits and the duality of Bayesian inference and optimal control

K. Doya, 2021, Current Opinion in Behavioral Sciences.

A Kinetic Model of Dopamine- and Calcium-Dependent Striatal Synaptic Plasticity

Junichiro Yoshimoto, Kenji Doya, Takashi Nakano, 2010, PLoS Comput. Biol..

Reinforcement learning with via-point representation

Jun Morimoto, Mitsuo Kawato, Kenji Doya, 2004, Neural Networks.

Estimating Internal Variables of a Decision Maker's Brain: A Model-Based Approach for Neuroscience

Kenji Doya, Kazuyuki Samejima, K. Doya, 2007, ICONIP.

Model-based action planning involves cortico-cerebellar and basal ganglia networks

Makoto Ito, Kenji Doya, Junichiro Yoshimoto, 2016, Scientific Reports.

25th Annual Computational Neuroscience Meeting: CNS-2016

Morten L. Kringelbach, Majid Nili Ahmadabadi, Anders M. Dale, 2016, BMC Neuroscience.

Multiple model-based reinforcement learning explains dopamine neuronal activity

Kenji Doya, Nicolas Schweighofer, Mathieu Bertin, 2007, Neural Networks.

Optimization and validation of diffusion MRI-based fiber tracking with neural tracer data as a reference

K. Doya, Y. Yamaguchi, S. Ishii, 2019, Scientific Reports.

Identification of depression subtypes and relevant brain regions using a data-driven approach

Kenji Doya, Junichiro Yoshimoto, Yasumasa Okamoto, 2018, Scientific Reports.

Emergence of Polymorphic Mating Strategies in Robot Colonies

Kenji Doya, Stefan Elfwing, K. Doya, 2014, PloS one.

Intrinsic Motivation in Creative Activity

K. Doya, Conor Stephens, 2021 .

Evidence for Model-Based Action Planning in a Sequential Finger Movement Task

Makoto Ito, Kenji Doya, Junichiro Yoshimoto, 2010, Journal of motor behavior.

fMRI investigation of cortical and subcortical networks in the learning of abstract and effector-specific representations of motor sequences

Kenji Doya, Raju S. Bapi, Krishna P. Miyapuram, 2006, NeuroImage.

A Study of Learning Algorithms for Continuous-TimeRecurrent Neural Networks

Kenji Doya, K. Doya, 1991 .

Neural network model of temporal pattern memory

Kenji Doya, Shuji Yoshizawa, K. Doya, 1991, Systems and Computers in Japan.

Maaping Between Neural and Physical Activities of the Lobster Gastric Mill

Kenji Doya, Allen I. Selverston, Mary E. T. Boyle, 1992, NIPS.

Toward evolutionary and developmental intelligence

Kenji Doya, Tadahiro Taniguchi, K. Doya, 2019, Current Opinion in Behavioral Sciences.

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..

Habits and goals in synergy: a variational Bayesian framework for behavior

K. Doya, J. Tani, Dongqi Han, 2023, ArXiv.

Goal-Directed Planning by Reinforcement Learning and Active Inference pdf

Dongqi Han, Kenji Doya, Jun Tani, 2021, ArXiv.

Variational Recurrent Models for Solving Partially Observable Control Tasks pdf

Dongqi Han, Kenji Doya, Jun Tani, 2019, ICLR.

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum

Makoto Ito, Kenji Doya, K. Doya, 2015, PLoS Comput. Biol..

Reinforcement learning: Computational theory and biological mechanisms

Kenji Doya, K. Doya, 2007, HFSP journal.

Hierarchical control of goal-directed action in the cortical–basal ganglia network

Kenji Doya, Amir Dezfouli, Bernard W Balleine, 2015, Current Opinion in Behavioral Sciences.

A learning algorithm for Hodgkin-Huxley type neuron models

K. Doya, A. I. Selverston, K. Doya, 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

Expedited review process

DeLiang Wang, John G. Taylor, Kenji Doya, 2012, Neural Networks.

Darwinian embodied evolution of the learning ability for survival

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

Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning

Jun Morimoto, Kenji Doya, K. Doya, 2000, Robotics Auton. Syst..

Title: The role of serotonin in waiting for future rewards in depression

Kjell Fuxe, Saori C. Tanaka, Carmelo Millón, 2016 .

Evolution of Neural Architecture Fitting Environmental Dynamics

Kenji Doya, Genci Capi, K. Doya, 2005, Adapt. Behav..

Chunking During Learning of Visuomotor Sequences with Spatial and Arbitrary Rules: Preliminary Findings

Krishna P. Miyapuram, K. Doya, R. Bapi, 2012 .

Chunking During Learning of Visuomotor Sequences with Spatial and Arbitrary Rules: Preliminary Findings

Krishna P. Miyapuram, K. Doya, R. Bapi, 2011, Psychological Studies.

Evolving recurrent neural controllers for sequential tasks: a parallel implementation

Kenji Doya, Genci Capi, K. Doya, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

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..

MarmoNet: a pipeline for automated projection mapping of the common marmoset brain from whole-brain serial two-photon tomography pdf

Shin Ishii, Ken Nakae, Kenji Doya, 2019, ArXiv.

Three-dimensional distribution of Fos-positive neurons in the supramammillary nucleus of the rat exposed to novel environment

Makoto Ito, Kenji Doya, Tomoaki Shirao, 2009, Neuroscience Research.

Neurons: A Compartmental Model Electrophysiological Properties of Inferior Olive

W. T. Thach, Simon Hong, K. Doya, 2011 .

Multi-objective Parameter Optimization of DWI-based Global Fiber Tracking with Neuronal Tracer Signal as a Reference

K. Doya, Y. Yamaguchi, S. Ishii, 2019 .

Brain mechanism of reward prediction under predictable and unpredictable environmental dynamics

Kenji Doya, Kazutaka Ueda, Yasumasa Okamoto, 2006, Neural Networks.

Driver model based on reinforced learning with multiple‐step state estimation

Kenji Doya, Yasuharu Koike, K. Doya, 2003 .

Effects of transcranial direct current stimulation in brain-computer interface

Takashi Hanakawa, Kenji Doya, Yousuke Ogata, 2021, 2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech).

Neurocomputational models of brain disorders

Wlodzislaw Duch, Kenji Doya, Vassilis Cutsuridis, 2011, Neural Networks.

Condition interference in rats performing a choice task with switched variable- and fixed-reward conditions

K. Doya, R. Kanzaki, Makoto Ito, 2015, Front. Neurosci..

Learning a dynamic policy by using policy gradient: application to biped walking

Jun Morimoto, Jun Nakanishi, Takamitsu Matsubara, 2007, Syst. Comput. Jpn..

Humans Can Adopt Optimal Discounting Strategy under Real-Time Constraints

Kenji Doya, Nicolas Schweighofer, Yasumasa Okamoto, 2006, PLoS Comput. Biol..

Computational Model of Recurrent Subthalamo-Pallidal Circuit for Generation of Parkinsonian Oscillations

Kenji Doya, Atsushi Nambu, Osamu Shouno, 2017, Front. Neuroanat..

Neural and Personality Correlates of Individual Differences Related to the Effects of Acute Tryptophan Depletion on Future Reward Evaluation

Saori C. Tanaka, K. Doya, N. Schweighofer, 2012, Neuropsychobiology.

Reward probability and timing uncertainty alter the effect of dorsal raphe serotonin neurons on patience

Kenji F. Tanaka, K. Doya, A. Yamanaka, 2018, Nature Communications.

Multiple model-based reinforcement learning for nonlinear control

Mitsuo Kawato, Kenji Doya, Kazuyuki Samejima, 2006 .

Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression

Kenji Doya, Kosuke Yoshida, Junichiro Yoshimoto, 2017, PloS one.

Combining Modalities with Different Latencies for Optimal Motor Control

Kenji Doya, Hiroyuki Nakahara, Okihide Hikosaka, 2008, Journal of Cognitive Neuroscience.

Neural Information Processing

Akira Hirose, Kazushi Ikeda, Kenji Doya, 2014, Lecture Notes in Computer Science.

Automated segmentation of insect anatomy from micro-CT images using deep learning

K. Doya, C. E. Gutierrez, E. Economo, 2021, bioRxiv.

Optogenetic activation of dorsal raphe serotonin neurons induces brain-wide activation, including reward-related circuits

Kenji F. Tanaka, K. Doya, N. Takata, 2023, bioRxiv.

The Role of Serotonin in the Regulation of Patience and Impulsivity

K. Doya, K. Miyazaki, Katsuhiko Miyazaki, 2012, Molecular Neurobiology.

Diffusion functional MRI reveals global brain network functional abnormalities driven by targeted local activity in a neuropsychiatric disease mouse model

Kenji Doya, Yuki Sakai, Denis Le Bihan, 2020, NeuroImage.

Serotonergic modulation of cognitive computations

K. Doya, K. Miyazaki, Katsuhiko Miyazaki, 2021, Current Opinion in Behavioral Sciences.

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 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.

Gap-Increasing Policy Evaluation for Efficient and Noise-Tolerant Reinforcement Learning pdf

Dongqi Han, Kenji Doya, Tadashi Kozuno, 2019, ArXiv.

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..

APPLICATION OF EVOLUTIONARY COMPUTATION FOR EFFICIENT REINFORCEMENT LEARNING

Kenji Doya, Genci Capi, K. Doya, 2006, Appl. Artif. Intell..

Robustness of linearly solvable Markov games employing inaccurate dynamics model

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