| Sigmoid-weighted linear units for neural network function approximation in reinforcement learning S Elfwing, E Uchibe, K Doya Neural networks 107, 3-11, 2018 | 1697 | 2018 |
| 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 | 1623 | 2003 |
| Reinforcement learning in continuous time and space K Doya Neural computation 12 (1), 219-245, 2000 | 1317 | 2000 |
| Complementary roles of basal ganglia and cerebellum in learning and motor control K Doya Current opinion in neurobiology 10 (6), 732-739, 2000 | 1235 | 2000 |
| Representation of action-specific reward values in the striatum K Samejima, Y Ueda, K Doya, M Kimura Science 310 (5752), 1337-1340, 2005 | 1144 | 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 | 1049 | 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 | 1049 | 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 | 1003 | 1999 |
| Bayesian brain: Probabilistic approaches to neural coding K Doya MIT press, 2007 | 926 | 2007 |
| Metalearning and neuromodulation K Doya Neural networks 15 (4-6), 495-506, 2002 | 863 | 2002 |
| Modulators of decision making K Doya Nature neuroscience 11 (4), 410-416, 2008 | 836 | 2008 |
| The computational neurobiology of learning and reward ND Daw, K Doya Current opinion in neurobiology 16 (2), 199-204, 2006 | 696 | 2006 |
| Multiple model-based reinforcement learning K Doya, K Samejima, K Katagiri, M Kawato Neural computation 14 (6), 1347-1369, 2002 | 652 | 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 | 458 | 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 | 388 | 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 | 372 | 2004 |
| Meta-learning in reinforcement learning N Schweighofer, K Doya Neural Networks 16 (1), 5-9, 2003 | 331 | 2003 |
| 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 | 326 | 2008 |
| 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 | 323 | 2004 |
| Robust reinforcement learning J Morimoto, K Doya Neural computation 17 (2), 335-359, 2005 | 314 | 2005 |
