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Jordi Grau-Moya
Jordi Grau-Moya
Research Scientist at Google DeepMind
Bestätigte E-Mail-Adresse bei deepmind.com - Startseite
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Neural networks and the chomsky hierarchy
G Delétang, A Ruoss, J Grau-Moya, T Genewein, LK Wenliang, E Catt, ...
arXiv preprint arXiv:2207.02098, 2022
1402022
Language Modeling Is Compression
G Delétang, A Ruoss, PA Duquenne, E Catt, T Genewein, C Mattern, ...
arXiv preprint arXiv:2309.10668, 2023
1392023
Bounded rationality, abstraction and hierarchical decision-making: an information-theoretic optimality principle
T Genewein, F Leibfried, J Grau-Moya, DAB Braun
Frontiers in Robotics and AI 2, 27, 2015
1262015
Randomized Positional Encodings Boost Length Generalization of Transformers
A Ruoss, G Delétang, T Genewein, J Grau-Moya, R Csordás, M Bennani, ...
arXiv preprint arXiv:2305.16843, 2023
832023
Shaking the foundations: delusions in sequence models for interaction and control
PA Ortega, M Kunesch, G Delétang, T Genewein, J Grau-Moya, J Veness, ...
arXiv preprint arXiv:2110.10819, 2021
662021
Soft Q-Learning with Mutual-Information Regularization
J Grau-Moya, F Leibfried, P Vrancx
International Conference on Learning Representations (ICLR), 2019
652019
Balancing Two-Player Stochastic Games with Soft Q-Learning
J Grau-Moya, F Leibfried, H Bou-Ammar
Proceedings of the 27th International Joint Conference on Artificial …, 2018
582018
Signaling equilibria in sensorimotor interactions.
F Leibfried, J Grau-Moya, DA Braun
Cognition 141, 73-86, 2015
492015
A unified bellman optimality principle combining reward maximization and empowerment
F Leibfried, S Pascual-Diaz, J Grau-Moya
Advances in Neural Information Processing Systems, 7869-7880, 2019
402019
Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes
J Grau-Moya, F Leibfried, T Genewein, DA Braun
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016
382016
Grandmaster-level chess without search
A Ruoss, G Delétang, S Medapati, J Grau-Moya, LK Wenliang, E Catt, ...
arXiv e-prints, arXiv: 2402.04494, 2024
332024
An information-theoretic optimality principle for deep reinforcement learning
F Leibfried, J Grau-Moya, H Bou-Ammar
NeurIPS Workshop on Deep Reinforcement Learning, 2017
322017
The effect of model uncertainty on cooperation in sensorimotor interactions
J Grau-Moya, E Hez, G Pezzulo, DA Braun
Journal of The Royal Society Interface 10 (87), 20130554, 2013
262013
Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning
F Leibfried, J Grau-Moya
Conference on Robot Learning (CoRL), 2019
252019
Risk-Sensitivity in Bayesian Sensorimotor Integration
J Grau-Moya, PA Ortega, DA Braun
PLOS Computational Biology 8 (9), e1002698, 2012
212012
Disentangled Skill Embeddings for Reinforcement Learning
JC Petangoda, S Pascual-Diaz, V Adam, P Vrancx, J Grau-Moya
NeurIPS Workshop on Learning Transferable Skills, 2019
202019
Model-Free Risk-Sensitive Reinforcement Learning
G Delétang, J Grau-Moya, M Kunesch, T Genewein, R Brekelmans, ...
arXiv preprint arXiv:2111.02907, 2021
132021
Non-equilibrium relations for bounded rational decision-making in changing environments
J Grau-Moya, M Krüger, DA Braun
Entropy 20 (1), 1, 2017
122017
Your Policy Regularizer is Secretly an Adversary
R Brekelmans, T Genewein, J Grau-Moya, G Delétang, M Kunesch, ...
arXiv preprint arXiv:2203.12592, 2022
112022
Causal Analysis of Agent Behavior for AI Safety
G Déletang, J Grau-Moya, M Martic, T Genewein, T McGrath, V Mikulik, ...
arXiv preprint arXiv:2103.03938, 2021
112021
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