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Ari Weinstein
Ari Weinstein
Deepmind
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Title
Cited by
Cited by
Year
Model-based hierarchical reinforcement learning and human action control
M Botvinick, A Weinstein
Philosophical Transactions of the Royal Society B: Biological Sciences 369 …, 2014
2132014
Sample-based planning for continuous action markov decision processes
C Mansley, A Weinstein, M Littman
Proceedings of the International Conference on Automated Planning and …, 2011
1142011
Reinforcement learning, efficient coding, and the statistics of natural tasks
M Botvinick, A Weinstein, A Solway, A Barto
Current opinion in behavioral sciences 5, 71-77, 2015
1122015
Bandit-based planning and learning in continuous-action markov decision processes
A Weinstein, M Littman
Proceedings of the International Conference on Automated Planning and …, 2012
952012
Intuitive physics learning in a deep-learning model inspired by developmental psychology
LS Piloto, A Weinstein, P Battaglia, M Botvinick
Nature human behaviour 6 (9), 1257-1267, 2022
792022
Human-centred mechanism design with Democratic AI
R Koster, J Balaguer, A Tacchetti, A Weinstein, T Zhu, O Hauser, ...
Nature Human Behaviour 6 (10), 1398-1407, 2022
562022
Open-loop planning in large-scale stochastic domains
A Weinstein, M Littman
Proceedings of the AAAI Conference on Artificial Intelligence 27 (1), 1436-1442, 2013
472013
Inferring the intentional states of autonomous virtual agents
PC Pantelis, CL Baker, SA Cholewiak, K Sanik, A Weinstein, CC Wu, ...
Cognition 130 (3), 360-379, 2014
432014
Probing physics knowledge using tools from developmental psychology
L Piloto, A Weinstein, D TB, A Ahuja, M Mirza, G Wayne, D Amos, C Hung, ...
arXiv preprint arXiv:1804.01128, 2018
312018
The cross-entropy method optimizes for quantiles
S Goschin, A Weinstein, M Littman
International Conference on Machine Learning, 1193-1201, 2013
172013
Structure learning in motor control: A deep reinforcement learning model
A Weinstein, MM Botvinick
arXiv preprint arXiv:1706.06827, 2017
132017
Agency and rationality: Adopting the intentional stance toward evolved virtual agents.
PC Pantelis, T Gerstner, K Sanik, A Weinstein, SA Cholewiak, G Kharkwal, ...
Decision 3 (1), 40, 2016
132016
Planning in reward-rich domains via PAC bandits
S Goschin, A Weinstein, ML Littman, E Chastain
European Workshop on Reinforcement Learning, 25-42, 2013
122013
Local planning for continuous Markov decision processes
A Weinstein
Rutgers The State University of New Jersey, School of Graduate Studies, 2014
112014
Sample-based planning for continuous action markov decision processes
A Weinstein, C Mansley, M Littman
ICML 2010 Workshop on Reinforcement Learning and Search in Very Large Spaces, 2010
102010
Perception of intentions and mental states in autonomous virtual agents
PC Pantelis, SA Cholewiak, P Ringstad, K Sanik, A Weinstein, CC Wu, ...
Proceedings of the Annual Meeting of the Cognitive Science Society 33 (33), 2011
92011
Rollout-based game-tree search outprunes traditional alpha-beta
A Weinstein, ML Littman, S Goschin
European Workshop on Reinforcement Learning, 155-167, 2013
52013
Hcmd-zero: Learning value aligned mechanisms from data
J Balaguer, R Koster, A Weinstein, L Campbell-Gillingham, ...
arXiv preprint arXiv:2202.10122, 2022
42022
Publisher Correction: Human-centred mechanism design with Democratic AI
R Koster, J Balaguer, A Tacchetti, A Weinstein, T Zhu, O Hauser, ...
Nature Human Behaviour 6 (9), 1320, 2022
22022
Publisher Correction: Intuitive physics learning in a deep-learning model inspired by developmental psychology
LS Piloto, A Weinstein, P Battaglia, M Botvinick
Nature Human Behaviour 6 (8), 1181, 2022
2022
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