Kenji Doya
Zitiert von
Zitiert von
A unifying computational framework for motor control and social interaction
DM Wolpert, K Doya, M Kawato
Philosophical Transactions of the Royal Society of London. Series B …, 2003
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
S Elfwing, E Uchibe, K Doya
Neural networks 107, 3-11, 2018
Reinforcement learning in continuous time and space
K Doya
Neural computation 12 (1), 219-245, 2000
Complementary roles of basal ganglia and cerebellum in learning and motor control
K Doya
Current opinion in neurobiology 10 (6), 732-739, 2000
Representation of action-specific reward values in the striatum
K Samejima, Y Ueda, K Doya, M Kimura
Science 310 (5752), 1337-1340, 2005
Prediction of immediate and future rewards differentially recruits cortico-basal ganglia loops
SC Tanaka, K Doya, G Okada, K Ueda, Y Okamoto, S Yamawaki
Behavioral economics of preferences, choices, and happiness, 593-616, 2016
What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?
K Doya
Neural networks 12 (7-8), 961-974, 1999
Parallel neural networks for learning sequential procedures
O Hikosaka, H Nakahara, MK Rand, K Sakai, X Lu, K Nakamura, ...
Trends in neurosciences 22 (10), 464-471, 1999
Bayesian brain: Probabilistic approaches to neural coding
K Doya
MIT press, 2007
Metalearning and neuromodulation
K Doya
Neural networks 15 (4-6), 495-506, 2002
Modulators of decision making
K Doya
Nature neuroscience 11 (4), 410-416, 2008
The computational neurobiology of learning and reward
ND Daw, K Doya
Current opinion in neurobiology 16 (2), 199-204, 2006
Multiple model-based reinforcement learning
K Doya, K Samejima, K Katagiri, M Kawato
Neural computation 14 (6), 1347-1369, 2002
Consensus paper: towards a systems-level view of cerebellar function: the interplay between cerebellum, basal ganglia, and cortex
D Caligiore, G Pezzulo, G Baldassarre, AC Bostan, PL Strick, K Doya, ...
The Cerebellum 16, 203-229, 2017
Acquisition of stand-up behavior by a real robot using hierarchical reinforcement learning
J Morimoto, K Doya
Robotics and Autonomous Systems 36 (1), 37-51, 2001
A neural correlate of reward-based behavioral learning in caudate nucleus: a functional magnetic resonance imaging study of a stochastic decision task
M Haruno, T Kuroda, K Doya, K Toyama, M Kimura, K Samejima, ...
Journal of Neuroscience 24 (7), 1660-1665, 2004
Low-serotonin levels increase delayed reward discounting in humans
N Schweighofer, M Bertin, K Shishida, Y Okamoto, SC Tanaka, ...
Journal of Neuroscience 28 (17), 4528-4532, 2008
Meta-learning in reinforcement learning
N Schweighofer, K Doya
Neural Networks 16 (1), 5-9, 2003
Hierarchical Bayesian estimation for MEG inverse problem
M Sato, T Yoshioka, S Kajihara, K Toyama, N Goda, K Doya, M Kawato
NeuroImage 23 (3), 806-826, 2004
Validation of decision-making models and analysis of decision variables in the rat basal ganglia
M Ito, K Doya
Journal of Neuroscience 29 (31), 9861-9874, 2009
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