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Markus Kunesch

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

Oct 12, 2022
Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Tim Genewein, Elliot Catt, Kevin Li, Anian Ruoss, Chris Cundy, Joel Veness, Jane Wang, Marcus Hutter, Christopher Summerfield, Shane Legg, Pedro Ortega

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* 33 pages, 8 figures, technical report

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Your Policy Regularizer is Secretly an Adversary

Apr 01, 2022
Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Grégoire Delétang, Markus Kunesch, Shane Legg, Pedro Ortega

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* 10 pages main text; added worked example

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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

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* 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

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* DeepMind Tech Report, 16 pages, 4 figures

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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

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* 16 pages, 16 figures, 6 tables

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Human-interpretable model explainability on high-dimensional data

Oct 14, 2020
Damien de Mijolla, Christopher Frye, Markus Kunesch, John Mansir, Ilya Feige

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* 8 pages, 6 figures, 1 appendix

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