Laurent Orseau

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 42

Top Topics

Asymptotic Optimality

Language Modeling

Convex Minimization

Top Venues

Publications

Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
Learning Universal Predictors. CoRR (2024)
Laurent Orseau, Remi Munos
Super-Exponential Regret for UCT, AlphaGo and Variants. CoRR (2024)
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
Language Modeling Is Compression. ICLR (2024)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. CoRR (2023)
Laurent Orseau, Marcus Hutter, Levi H. S. Lelis
Levin Tree Search with Context Models. CoRR (2023)
Laurent Orseau, Marcus Hutter
Line Search for Convex Minimization. CoRR (2023)
Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Matej Balog, Gheorghe Comanici, Tudor Berariu, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera-Paredes, Petar Velickovic, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner
Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search. CoRR (2023)
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
Language Modeling Is Compression. CoRR (2023)
Laurent Orseau, Marcus Hutter, Levi H. S. Lelis
Levin Tree Search with Context Models. IJCAI (2023)
Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
Memory-Based Meta-Learning on Non-Stationary Distributions. ICML (2023)
Eser Aygün, Ankit Anand, Laurent Orseau, Xavier Glorot, Stephen M. Mcaleer, Vlad Firoiu, Lei M. Zhang, Doina Precup, Shibl Mourad
Proving Theorems using Incremental Learning and Hindsight Experience Replay. ICML (2022)
Vlad Firoiu, Eser Aygün, Ankit Anand, Zafarali Ahmed, Xavier Glorot, Laurent Orseau, Lei M. Zhang, Doina Precup, Shibl Mourad
Training a First-Order Theorem Prover from Synthetic Data. CoRR (2021)
Laurent Orseau, Levi H. S. Lelis
Policy-Guided Heuristic Search with Guarantees. AAAI (2021)
Eser Aygün, Laurent Orseau, Ankit Anand, Xavier Glorot, Vlad Firoiu, Lei M. Zhang, Doina Precup, Shibl Mourad
Proving Theorems using Incremental Learning and Hindsight Experience Replay. CoRR (2021)
Laurent Orseau, Marcus Hutter
Isotuning With Applications To Scale-Free Online Learning. CoRR (2021)
Laurent Orseau, Levi H. S. Lelis
Policy-Guided Heuristic Search with Guarantees. CoRR (2021)
Victoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg
Avoiding Side Effects By Considering Future Tasks. CoRR (2020)
Laurent Orseau, Marcus Hutter, Omar Rivasplata
Logarithmic Pruning is All You Need. NeurIPS (2020)
Laurent Orseau, Marcus Hutter, Omar Rivasplata
Logarithmic Pruning is All You Need. CoRR (2020)
Victoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg
Avoiding Side Effects By Considering Future Tasks. NeurIPS (2020)
Stuart Armstrong, Jan Leike, Laurent Orseau, Shane Legg
Pitfalls of Learning a Reward Function Online. IJCAI (2020)
Eser Aygün, Zafarali Ahmed, Ankit Anand, Vlad Firoiu, Xavier Glorot, Laurent Orseau, Doina Precup, Shibl Mourad
Learning to Prove from Synthetic Theorems. CoRR (2020)
Stuart Armstrong, Jan Leike, Laurent Orseau, Shane Legg
Pitfalls of learning a reward function online. CoRR (2020)
Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau, Nathan R. Sturtevant
Iterative Budgeted Exponential Search. IJCAI (2019)
Laurent Orseau, Tor Lattimore, Shane Legg
Soft-Bayes: Prod for Mixtures of Experts with Log-Loss. CoRR (2019)
Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Théophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap
An investigation of model-free planning. CoRR (2019)
Arthur Guez, Mehdi Mirza, Karol Gregor, Rishabh Kabra, Sébastien Racanière, Theophane Weber, David Raposo, Adam Santoro, Laurent Orseau, Tom Eccles, Greg Wayne, David Silver, Timothy P. Lillicrap
An Investigation of Model-Free Planning. ICML (2019)
Laurent Orseau, Levi H. S. Lelis, Tor Lattimore
Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees. CoRR (2019)
Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau, Nathan R. Sturtevant
Iterative Budgeted Exponential Search. CoRR (2019)
Victoria Krakovna, Laurent Orseau, Miljan Martic, Shane Legg
Penalizing Side Effects using Stepwise Relative Reachability. AISafety@IJCAI (2019)
Victoria Krakovna, Laurent Orseau, Miljan Martic, Shane Legg
Measuring and avoiding side effects using relative reachability. CoRR (2018)
Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber
Single-Agent Policy Tree Search With Guarantees. NeurIPS (2018)
Laurent Orseau, Levi H. S. Lelis, Tor Lattimore, Théophane Weber
Single-Agent Policy Tree Search With Guarantees. CoRR (2018)
Laurent Orseau, Simon McGregor McGill, Shane Legg
Agents and Devices: A Relative Definition of Agency. CoRR (2018)
Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
On Thompson Sampling and Asymptotic Optimality. IJCAI (2017)
Jan Leike, Miljan Martic, Victoria Krakovna, Pedro A. Ortega, Tom Everitt, Andrew Lefrancq, Laurent Orseau, Shane Legg
AI Safety Gridworlds. CoRR (2017)
Laurent Orseau, Tor Lattimore, Shane Legg
Soft-Bayes: Prod for Mixtures of Experts with Log-Loss. ALT (2017)
Tom Everitt, Victoria Krakovna, Laurent Orseau, Marcus Hutter, Shane Legg
Reinforcement Learning with a Corrupted Reward Channel. CoRR (2017)
Tom Everitt, Victoria Krakovna, Laurent Orseau, Shane Legg
Reinforcement Learning with a Corrupted Reward Channel. IJCAI (2017)
Laurent Orseau, Stuart Armstrong
Safely Interruptible Agents. UAI (2016)
Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
Thompson Sampling is Asymptotically Optimal in General Environments. UAI (2016)
Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
Thompson Sampling is Asymptotically Optimal in General Environments. CoRR (2016)
Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare
Online Learning of k-CNF Boolean Functions. IJCAI (2015)
Laurent Orseau
Universal knowledge-seeking agents. Theor. Comput. Sci. 519 (2014)
Laurent Orseau
The Multi-slot Framework: A Formal Model for Multiple, Copiable AIs. AGI (2014)
Laurent Orseau
Teleporting Universal Intelligent Agents. AGI (2014)
Laurent Orseau, Tor Lattimore, Marcus Hutter
Universal Knowledge-Seeking Agents for Stochastic Environments. ALT (2013)
Laurent Orseau
Asymptotic non-learnability of universal agents with computable horizon functions. Theor. Comput. Sci. 473 (2013)
Peter Auer, Marcus Hutter, Laurent Orseau
Reinforcement Learning (Dagstuhl Seminar 13321). Dagstuhl Reports 3 (8) (2013)
Laurent Orseau, Mark B. Ring
Space-Time Embedded Intelligence. AGI (2012)
Laurent Orseau, Mark B. Ring
Memory Issues of Intelligent Agents. AGI (2012)
Laurent Orseau
Universal Knowledge-Seeking Agents. ALT (2011)
Mark B. Ring, Laurent Orseau
Delusion, Survival, and Intelligent Agents. AGI (2011)
Laurent Orseau, Mark B. Ring
Self-Modification and Mortality in Artificial Agents. AGI (2011)
Laurent Orseau
Optimality Issues of Universal Greedy Agents with Static Priors. ALT (2010)
Laurent Orseau
Learning to Count by Think Aloud Imitation. IJCAI (2007)
Laurent Orseau
Short Term Memories and Forcing the Re-use of Knowledge for Generalization. ICANN (2) (2005)