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 001 (NIPS, 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)

Risk-Sensitivity in Bayesian Sensorimotor Integration. - Jordi Grau-Moya; Pedro A. Ortega; Daniel A. Braun 001 (PLoS Comput. Biol., 2012)

Bounded Rational Decision-Making in Changing Environments. - Jordi Grau-Moya; Daniel A. Braun 001 (CoRR, 2013)

Adaptive information-theoretic bounded rational decision-making with parametric priors. - Jordi Grau-Moya; Daniel A. Braun 001 (CoRR, 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)

Planning with Information-Processing Constraints and Model Uncertainty in Markov Decision Processes. - Jordi Grau-Moya; Felix Leibfried; Tim Genewein; Daniel A. Braun 001 (ECML/PKDD (2), 2016)

An Information-Theoretic Optimality Principle for Deep Reinforcement Learning. - Felix Leibfried; Jordi Grau-Moya; Haitham Bou-Ammar (CoRR, 2017)

Decision-Making under Bounded Rationality and Model Uncertainty: an Information-Theoretic Approach - Jordi Grau-Moya (2017)

Balancing Two-Player Stochastic Games with Soft Q-Learning. - Jordi Grau-Moya; Felix Leibfried; Haitham Bou-Ammar (IJCAI, 2018)

Non-Equilibrium Relations for Bounded Rational Decision-Making in Changing Environments. - Jordi Grau-Moya; Matthias Krüger; Daniel A. Braun 001 (Entropy, 2018)

Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning. - Felix Leibfried; Jordi Grau-Moya (CoRL, 2019)

Soft Q-Learning with Mutual-Information Regularization. - Jordi Grau-Moya; Felix Leibfried; Peter Vrancx (ICLR (Poster), 2019)

A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment. - Felix Leibfried; Sergio Pascual-Diaz; Jordi Grau-Moya (NeurIPS, 2019)

Disentangled Skill Embeddings for Reinforcement Learning. - Janith C. Petangoda; Sergio Pascual-Diaz; Vincent Adam; Peter Vrancx; Jordi Grau-Moya (CoRR, 2019)

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)

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)

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; et al. (CoRR, 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)

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)

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; et al. (CoRR, 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)

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 (ACL (2), 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 (ICLR, 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 (ICML, 2023)

Self-Predictive Universal AI. - Elliot Catt; Jordi Grau-Moya; Marcus Hutter; Matthew Aitchison; Tim Genewein; Grégoire Delétang; Kevin Li; Joel Veness (NeurIPS, 2023)

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 (ICLR, 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 (ICML, 2024)

Amortized Planning with Large-Scale Transformers: A Case Study on Chess. - Anian Ruoss; Grégoire Delétang; Sourabh Medapati; Jordi Grau-Moya; Kevin Li; Elliot Catt; John Reid; Cannada Lewis; Joel Veness; Tim Genewein (NeurIPS, 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)

Why is prompting hard? Understanding prompts on binary sequence predictors. - Li Kevin Wenliang; Anian Ruoss; Jordi Grau-Moya; Marcus Hutter; Tim Genewein (CoRR, 2025)

Partition Tree Weighting for Non-Stationary Stochastic Bandits. - Joel Veness; Marcus Hutter; András György 001; Jordi Grau-Moya (CoRR, 2025)

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities. - Thomas Schmied; Jörg Bornschein; Jordi Grau-Moya; Markus Wulfmeier; Razvan Pascanu (CoRR, 2025)

Understanding Prompt Tuning and In-Context Learning via Meta-Learning. - Tim Genewein; Li Kevin Wenliang; Jordi Grau-Moya; Anian Ruoss; Laurent Orseau; Marcus Hutter (CoRR, 2025)