Jordi Grau-Moya

According to our database, Jordi Grau-Moya authored at least 29 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Grandmaster-Level Chess Without Search.

Anian Ruoss, Grégoire Delétang, Sourabh Medapati, Jordi Grau-Moya, Li Kevin Wenliang, Elliot Catt, John Reid, Tim Genewein

CoRR, 2024

Learning Universal Predictors.

Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Language Modeling Is Compression.

Grégoire Delétang, Anian Ruoss, Paul-Ambroise Duquenne, Elliot Catt, Tim Genewein, Christopher Mattern, Jordi Grau-Moya, Li Kevin Wenliang, Matthew Aitchison, Laurent Orseau, Marcus Hutter, Joel Veness

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Self-Predictive Universal AI.

Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Memory-Based Meta-Learning on Non-Stationary Distributions.

Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness

Proceedings of the International Conference on Machine Learning, 2023

Neural Networks and the Chomsky Hierarchy.

Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Chris Cundy, Marcus Hutter, Shane Legg, Joel Veness, Pedro A. Ortega

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Randomized Positional Encodings Boost Length Generalization of Transformers.

Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, Joel Veness

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

2022

Your Policy Regularizer is Secretly an Adversary.

Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro A. Ortega

Trans. Mach. Learn. Res., 2022

Beyond Bayes-optimality: meta-learning what you know you don't know.

Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane X. Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro A. Ortega

CoRR, 2022

Neural Networks and the Chomsky Hierarchy.

Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega

CoRR, 2022

2021

Model-Free Risk-Sensitive Reinforcement Learning.

Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega

CoRR, 2021

Shaking the foundations: delusions in sequence models for interaction and control.

Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Pérolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg

CoRR, 2021

Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow.

John McLeod, Hrvoje Stojic, Vincent Adam, Dongho Kim, Jordi Grau-Moya, Peter Vrancx, Felix Leibfried

CoRR, 2021

Causal Analysis of Agent Behavior for AI Safety.

Grégoire Delétang, Jordi Grau-Moya, Miljan Martic, Tim Genewein, Tom McGrath, Vladimir Mikulik, Markus Kunesch, Shane Legg, Pedro A. Ortega

CoRR, 2021

2019

Disentangled Skill Embeddings for Reinforcement Learning.

Janith C. Petangoda, Sergio Pascual-Diaz, Vincent Adam, Peter Vrancx, Jordi Grau-Moya

CoRR, 2019

A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment.

Felix Leibfried, Sergio Pascual-Diaz, Jordi Grau-Moya

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Soft Q-Learning with Mutual-Information Regularization.

Jordi Grau-Moya, Felix Leibfried, Peter Vrancx

Proceedings of the 7th International Conference on Learning Representations, 2019

Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning.

Felix Leibfried, Jordi Grau-Moya

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

2018

Non-Equilibrium Relations for Bounded Rational Decision-Making in Changing Environments.

Jordi Grau-Moya, Matthias Krüger, Daniel A. Braun

Entropy, 2018

Balancing Two-Player Stochastic Games with Soft Q-Learning.

Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

Decision-Making under Bounded Rationality and Model Uncertainty: an Information-Theoretic Approach

Jordi Grau-Moya

PhD thesis, 2017

An Information-Theoretic Optimality Principle for Deep Reinforcement Learning.

Felix Leibfried, Jordi Grau-Moya, Haitham Bou-Ammar

CoRR, 2017

2016

Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes.

Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2016

2015

Bounded Rationality, Abstraction, and Hierarchical Decision-Making: An Information-Theoretic Optimality Principle.

Tim Genewein, Felix Leibfried, Jordi Grau-Moya, Daniel Alexander Braun

Frontiers Robotics AI, 2015

Adaptive information-theoretic bounded rational decision-making with parametric priors.

Jordi Grau-Moya, Daniel A. Braun

CoRR, 2015

2013

Bounded Rational Decision-Making in Changing Environments.

Jordi Grau-Moya, Daniel A. Braun

CoRR, 2013

2012

Risk-Sensitivity in Bayesian Sensorimotor Integration.

Jordi Grau-Moya, Pedro A. Ortega, Daniel A. Braun

PLoS Comput. Biol., 2012

Noise-induced up/Down Dynamics in Scale-Free neuronal Networks.

Jordi Grau-Moya, Antonio J. Pons Rivero, Jordi García-Ojalvo

Int. J. Bifurc. Chaos, 2012

A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function.

Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012