An object-oriented representation for efficient reinforcement learning C Diuk, A Cohen, ML Littman Proceedings of the 25th international conference on Machine learning, 240-247, 2008 | 384 | 2008 |
Optimal behavioral hierarchy A Solway, C Diuk, N Córdova, D Yee, AG Barto, Y Niv, MM Botvinick PLOS Computational Biology 10 (8), e1003779, 2014 | 222 | 2014 |
A neural signature of hierarchical reinforcement learning JÚJF Ribas-Fernandes, A Solway, C Diuk, JT McGuire, AG Barto, Y Niv, ... Neuron 71 (2), 370-379, 2011 | 216 | 2011 |
Efficient structure learning in factored-state MDPs AL Strehl, C Diuk, ML Littman AAAI 7, 645-650, 2007 | 170 | 2007 |
Exploring compact reinforcement-learning representations with linear regression TJ Walsh, I Szita, C Diuk, ML Littman Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial …, 2009 | 133 | 2009 |
The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning C Diuk, L Li, BR Leffler Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 121 | 2009 |
Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia C Diuk, K Tsai, J Wallis, M Botvinick, Y Niv Journal of Neuroscience 33 (13), 5797-5805, 2013 | 99 | 2013 |
An adaptive anomaly detector for worm detection JM Agosta, C Diuk-Wasser, J Chandrashekar, C Livadas Proceedings of the 2nd USENIX workshop on Tackling computer systems problems …, 2007 | 54 | 2007 |
Divide and conquer: hierarchical reinforcement learning and task decomposition in humans C Diuk, A Schapiro, N Córdova, J Ribas-Fernandes, Y Niv, M Botvinick Computational and Robotic Models of the Hierarchical Organization of …, 2013 | 47 | 2013 |
A quantitative philology of introspection CG Diuk, DF Slezak, I Raskovsky, M Sigman, GA Cecchi Frontiers in integrative neuroscience 6, 80, 2012 | 46 | 2012 |
Generalizing apprenticeship learning across hypothesis classes TJ Walsh, K Subramanian, ML Littman, C Diuk Proceedings of the Twenty-Seventh International Conference on Machine …, 2010 | 36 | 2010 |
A hierarchical approach to efficient reinforcement learning in deterministic domains C Diuk, AL Strehl, ML Littman Proceedings of the fifth international joint conference on Autonomous agents …, 2006 | 33 | 2006 |
Compositional Policy Priors D Wingate, C Diuk, T O'Donnell, J Tenenbaum, S Gershman | 16 | 2013 |
The emergence of the modern concept of introspection: a quantitative linguistic analysis I Raskovsky, DF Slezak, CG Diuk, GA Cecchi Proceedings of the NAACL HLT 2010 Young Investigators Workshop on …, 2010 | 11 | 2010 |
An object-oriented representation for efficient reinforcement learning CGD Wasser Rutgers The State University of New Jersey-New Brunswick, 2010 | 9 | 2010 |
Social Catalysts: Characterizing People Who Spark Conversations Among Others M Saveski, F Kooti, S Morelli Vitousek, C Diuk, B Bartlett, LA Adamic Proceedings of the ACM on Human-Computer Interaction 5 (CSCW2), 1-20, 2021 | 6 | 2021 |
A hierarchical approach to efficient reinforcement learning ML Littman, C Diuk, A Strehl Proceedings of the ICML’05 Workshop on Rich Representations for …, 2005 | 6 | 2005 |
Parsing Heuristic and Forward Search in First‐Graders' Game‐Play Behavior L Paz, AP Goldin, C Diuk, M Sigman Cognitive science 39 (5), 944-971, 2015 | 5 | 2015 |
Hierarchical Reinforcement Learning. C Diuk, ML Littman Encyclopedia of Artificial Intelligence, 825-830, 2009 | 5 | 2009 |
Hierarchical reinforcement learning: an fMRI study of learning in a two-level gambling task C Diuk, AG Barto, MB Botvinick, Y Niv Soc Neurosci Abstr 36 (907.14), 2010 | 4 | 2010 |