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Model-Free Risk-Sensitive Reinforcement Learning


Nov 04, 2021
Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega

* DeepMind Tech Report: 13 pages, 4 figures 

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


Oct 20, 2021
Pedro A. Ortega, Markus Kunesch, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Joel Veness, Jonas Buchli, Jonas Degrave, Bilal Piot, Julien Perolat, Tom Everitt, Corentin Tallec, Emilio Parisotto, Tom Erez, Yutian Chen, Scott Reed, Marcus Hutter, Nando de Freitas, Shane Legg

* DeepMind Tech Report, 16 pages, 4 figures 

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


Apr 13, 2021
John McLeod, Hrvoje Stojic, Vincent Adam, Dongho Kim, Jordi Grau-Moya, Peter Vrancx, Felix Leibfried


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Causal Analysis of Agent Behavior for AI Safety


Mar 05, 2021
Grégoire Déletang, Jordi Grau-Moya, Miljan Martic, Tim Genewein, Tom McGrath, Vladimir Mikulik, Markus Kunesch, Shane Legg, Pedro A. Ortega

* 16 pages, 16 figures, 6 tables 

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


Sep 11, 2019
Felix Leibfried, Jordi Grau-Moya

* Proceedings of the 3rd Conference on Robot Learning (CoRL), Osaka, Japan, 2019 

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A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment


Sep 09, 2019
Felix Leibfried, Sergio Pascual-Diaz, Jordi Grau-Moya

* Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, 2019 

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Disentangled Skill Embeddings for Reinforcement Learning


Jun 21, 2019
Janith C. Petangoda, Sergio Pascual-Diaz, Vincent Adam, Peter Vrancx, Jordi Grau-Moya


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Regularised Deep Reinforcement Learning with Guaranteed Convergence


Sep 06, 2018
Felix Leibfried, Rasul Tutunov, Jordi Grau-Moya, Haitham Bou-Ammar


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Balancing Two-Player Stochastic Games with Soft Q-Learning


Feb 09, 2018
Jordi Grau-Moya, Felix Leibfried, Haitham Bou-Ammar


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


Apr 07, 2016
Jordi Grau-Moya, Felix Leibfried, Tim Genewein, Daniel A. Braun

* 16 pages, 3 figures 

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


Nov 05, 2015
Jordi Grau-Moya, Daniel A. Braun

* 4 pages, 1 figure, Workshop on Bounded Optimality and Rational Metareasoning at Neural Information Processing Systems conference, Montreal, Canada, 2015 

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Bounded Rational Decision-Making in Changing Environments


Dec 24, 2013
Jordi Grau-Moya, Daniel A. Braun

* 9 pages, 2 figures, NIPS 2013 Workshop on Planning with Information Constraints 

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


Nov 10, 2012
Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein, David Balduzzi, Daniel A. Braun

* Neural Information Processing Systems (NIPS) 2012 
* 9 pages, 5 figures 

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