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ORCIDLaurent Orseau
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2020 – today
- 2024
[c31]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- [c30]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. ICML 2024 - [c29]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. IJCAI 2024: 6985-6993 - [i26]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 abs/2401.14953 (2024) - [i25]Laurent Orseau, Rémi Munos:
Super-Exponential Regret for UCT, AlphaGo and Variants. CoRR abs/2405.04407 (2024) - 2023
- [c28]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: 11173-11195 - [c27]Laurent Orseau, Marcus Hutter, Levi H. S. Lelis:
Levin Tree Search with Context Models. IJCAI 2023: 5622-5630 - [i24]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 abs/2302.03067 (2023) - [i23]Laurent Orseau, Marcus Hutter, Levi H. S. Lelis:
Levin Tree Search with Context Models. CoRR abs/2305.16945 (2023) - [i22]Laurent Orseau, Marcus Hutter:
Line Search for Convex Minimization. CoRR abs/2307.16560 (2023) - [i21]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 abs/2309.10668 (2023) - [i20]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 abs/2311.03583 (2023) - 2022
- [c26]Eser Aygün, Ankit Anand, Laurent Orseau, Xavier Glorot
, Stephen Marcus McAleer, Vlad Firoiu, Lei M. Zhang, Doina Precup, Shibl Mourad:
Proving Theorems using Incremental Learning and Hindsight Experience Replay. ICML 2022: 1198-1210 - 2021
- [c25]Laurent Orseau, Levi H. S. Lelis:
Policy-Guided Heuristic Search with Guarantees. AAAI 2021: 12382-12390 - [i19]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 abs/2103.03798 (2021) - [i18]Laurent Orseau, Levi H. S. Lelis:
Policy-Guided Heuristic Search with Guarantees. CoRR abs/2103.11505 (2021) - [i17]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 abs/2112.10664 (2021) - [i16]Laurent Orseau, Marcus Hutter:
Isotuning With Applications To Scale-Free Online Learning. CoRR abs/2112.14586 (2021) - 2020
- [c24]Stuart Armstrong, Jan Leike, Laurent Orseau, Shane Legg:
Pitfalls of Learning a Reward Function Online. IJCAI 2020: 1592-1600 - [c23]Victoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg:
Avoiding Side Effects By Considering Future Tasks. NeurIPS 2020 - [c22]Laurent Orseau, Marcus Hutter, Omar Rivasplata:
Logarithmic Pruning is All You Need. NeurIPS 2020 - [i15]Stuart Armstrong, Jan Leike, Laurent Orseau, Shane Legg:
Pitfalls of learning a reward function online. CoRR abs/2004.13654 (2020) - [i14]Eser Aygün, Zafarali Ahmed, Ankit Anand, Vlad Firoiu, Xavier Glorot, Laurent Orseau, Doina Precup, Shibl Mourad:
Learning to Prove from Synthetic Theorems. CoRR abs/2006.11259 (2020) - [i13]Laurent Orseau, Marcus Hutter, Omar Rivasplata:
Logarithmic Pruning is All You Need. CoRR abs/2006.12156 (2020) - [i12]Victoria Krakovna, Laurent Orseau, Richard Ngo, Miljan Martic, Shane Legg:
Avoiding Side Effects By Considering Future Tasks. CoRR abs/2010.07877 (2020)
2010 – 2019
- 2019
- [c21]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: 2464-2473 - [c20]Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau, Nathan R. Sturtevant:
Iterative Budgeted Exponential Search. IJCAI 2019: 1249-1257 - [c19]Victoria Krakovna, Laurent Orseau, Miljan Martic, Shane Legg:
Penalizing Side Effects using Stepwise Relative Reachability. AISafety@IJCAI 2019 - [i11]Laurent Orseau, Tor Lattimore, Shane Legg:
Soft-Bayes: Prod for Mixtures of Experts with Log-Loss. CoRR abs/1901.02230 (2019) - [i10]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 abs/1901.03559 (2019) - [i9]Laurent Orseau, Levi H. S. Lelis, Tor Lattimore:
Zooming Cautiously: Linear-Memory Heuristic Search With Node Expansion Guarantees. CoRR abs/1906.03242 (2019) - [i8]Malte Helmert, Tor Lattimore, Levi H. S. Lelis, Laurent Orseau, Nathan R. Sturtevant:
Iterative Budgeted Exponential Search. CoRR abs/1907.13062 (2019) - 2018
- [c18]Laurent Orseau, Levi Lelis, Tor Lattimore, Theophane Weber:
Single-Agent Policy Tree Search With Guarantees. NeurIPS 2018: 3205-3215 - [i7]Laurent Orseau, Simon McGregor McGill, Shane Legg:
Agents and Devices: A Relative Definition of Agency. CoRR abs/1805.12387 (2018) - [i6]Victoria Krakovna, Laurent Orseau, Miljan Martic, Shane Legg:
Measuring and avoiding side effects using relative reachability. CoRR abs/1806.01186 (2018) - [i5]Laurent Orseau, Levi H. S. Lelis, Tor Lattimore, Théophane Weber:
Single-Agent Policy Tree Search With Guarantees. CoRR abs/1811.10928 (2018) - 2017
- [c17]Laurent Orseau, Tor Lattimore, Shane Legg:
Soft-Bayes: Prod for Mixtures of Experts with Log-Loss. ALT 2017: 372-399 - [c16]Tom Everitt, Victoria Krakovna, Laurent Orseau, Shane Legg:
Reinforcement Learning with a Corrupted Reward Channel. IJCAI 2017: 4705-4713 - [c15]Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter:
On Thompson Sampling and Asymptotic Optimality. IJCAI 2017: 4889-4893 - [i4]Tom Everitt, Victoria Krakovna, Laurent Orseau, Marcus Hutter, Shane Legg:
Reinforcement Learning with a Corrupted Reward Channel. CoRR abs/1705.08417 (2017) - [i3]Jan Leike, Miljan Martic, Victoria Krakovna, Pedro A. Ortega, Tom Everitt, Andrew Lefrancq, Laurent Orseau, Shane Legg:
AI Safety Gridworlds. CoRR abs/1711.09883 (2017) - 2016
- [c14]Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter:
Thompson Sampling is Asymptotically Optimal in General Environments. UAI 2016 - [c13]Laurent Orseau, Stuart Armstrong:
Safely Interruptible Agents. UAI 2016 - [i2]Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter:
Thompson Sampling is Asymptotically Optimal in General Environments. CoRR abs/1602.07905 (2016) - 2015
- [c12]Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare:
Online Learning of k-CNF Boolean Functions. IJCAI 2015: 3865-3873 - 2014
- [j2]Laurent Orseau:
Universal knowledge-seeking agents. Theor. Comput. Sci. 519: 127-139 (2014) - [c11]Laurent Orseau:
The Multi-slot Framework: A Formal Model for Multiple, Copiable AIs. AGI 2014: 97-108 - [c10]Laurent Orseau:
Teleporting Universal Intelligent Agents. AGI 2014: 109-120 - [e1]Ben Goertzel, Laurent Orseau, Javier Snaider:
Artificial General Intelligence - 7th International Conference, AGI 2014, Quebec City, QC, Canada, August 1-4, 2014. Proceedings. Lecture Notes in Computer Science 8598, Springer 2014, ISBN 978-3-319-09273-7 [contents] - 2013
- [j1]Laurent Orseau:
Asymptotic non-learnability of universal agents with computable horizon functions. Theor. Comput. Sci. 473: 149-156 (2013) - [c9]Laurent Orseau, Tor Lattimore, Marcus Hutter:
Universal Knowledge-Seeking Agents for Stochastic Environments. ALT 2013: 158-172 - [i1]Peter Auer, Marcus Hutter, Laurent Orseau:
Reinforcement Learning (Dagstuhl Seminar 13321). Dagstuhl Reports 3(8): 1-26 (2013) - 2012
- [c8]Laurent Orseau, Mark B. Ring:
Space-Time Embedded Intelligence. AGI 2012: 209-218 - [c7]Laurent Orseau, Mark B. Ring:
Memory Issues of Intelligent Agents. AGI 2012: 219-231 - 2011
- [c6]Laurent Orseau, Mark B. Ring:
Self-Modification and Mortality in Artificial Agents. AGI 2011: 1-10 - [c5]Mark B. Ring, Laurent Orseau:
Delusion, Survival, and Intelligent Agents. AGI 2011: 11-20 - [c4]Laurent Orseau:
Universal Knowledge-Seeking Agents. ALT 2011: 353-367 - 2010
- [c3]Laurent Orseau:
Optimality Issues of Universal Greedy Agents with Static Priors. ALT 2010: 345-359
2000 – 2009
- 2007
- [b1]Laurent Orseau:
Imitation algorithmique: apprentissage incrémental en-ligne de séquences. (Algorithmic imitation: online incremental leaning of sequences). University of Rennes 1, France, 2007 - [c2]Laurent Orseau:
Learning to Count by Think Aloud Imitation. IJCAI 2007: 1005-1010 - 2005
- [c1]Laurent Orseau:
Short Term Memories and Forcing the Re-use of Knowledge for Generalization. ICANN (2) 2005: 39-44
Coauthor Index
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last updated on 2024-10-21 21:26 CEST by the dblp team
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