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ORCIDMarcus Hutter
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- affiliation: Australian National University, Canberra, Australia
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2020 – today
- 2023
[c125]Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter:
Universal Agent Mixtures and the Geometry of Intelligence. AISTATS 2023: 4231-4246- [c124]Jörg Bornschein, Yazhe Li, Marcus Hutter:
Sequential Learning of Neural Networks for Prequential MDL. ICLR 2023 - [c123]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:
Neural Networks and the Chomsky Hierarchy. ICLR 2023 - [c122]Yazhe Li, Jörg Bornschein, Marcus Hutter:
Evaluating Representations with Readout Model Switching. ICLR 2023 - [c121]Matthew Aitchison, Penny Sweetser, Marcus Hutter:
Atari-5: Distilling the Arcade Learning Environment down to Five Games. ICML 2023: 421-438 - [c120]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 - [c119]Laurent Orseau, Marcus Hutter, Levi H. S. Lelis:
Levin Tree Search with Context Models. IJCAI 2023: 5622-5630 - [i170]Bryn Elesedy, Marcus Hutter:
U-Clip: On-Average Unbiased Stochastic Gradient Clipping. CoRR abs/2302.02971 (2023) - [i169]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) - [i168]Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter:
Universal Agent Mixtures and the Geometry of Intelligence. CoRR abs/2302.06083 (2023) - [i167]Yazhe Li, Jörg Bornschein, Marcus Hutter:
Evaluating Representations with Readout Model Switching. CoRR abs/2302.09579 (2023) - [i166]Laurent Orseau, Marcus Hutter, Levi H. S. Lelis:
Levin Tree Search with Context Models. CoRR abs/2305.16945 (2023) - [i165]Jonathon Schwartz, Hanna Kurniawati, Marcus Hutter:
Combining a Meta-Policy and Monte-Carlo Planning for Scalable Type-Based Reasoning in Partially Observable Environments. CoRR abs/2306.06067 (2023) - [i164]Laurent Orseau, Marcus Hutter:
Line Search for Convex Minimization. CoRR abs/2307.16560 (2023) - 2022
- [j49]Michael K. Cohen
, Marcus Hutter, Michael A. Osborne:
Advanced Artificial Agents Intervene in the Provision of Reward. AI Mag. 43(3): 282-293 (2022) - [j48]Michael K. Cohen, Marcus Hutter, Neel Nanda:
Fully General Online Imitation Learning. J. Mach. Learn. Res. 23: 334:1-334:30 (2022) - [c118]Elliot Catt, Marcus Hutter, Joel Veness:
Reinforcement Learning with Information-Theoretic Actuation. AGI 2022: 188-198 - [c117]Tomer Galanti, András György, Marcus Hutter:
On the Role of Neural Collapse in Transfer Learning. ICLR 2022 - [i163]Marcus Hutter, Steven Hansen:
Uniqueness and Complexity of Inverse MDP Models. CoRR abs/2206.01192 (2022) - [i162]Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega:
Neural Networks and the Chomsky Hierarchy. CoRR abs/2207.02098 (2022) - [i161]Mary Phuong, Marcus Hutter:
Formal Algorithms for Transformers. CoRR abs/2207.09238 (2022) - [i160]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, Shane Legg, Pedro A. Ortega:
Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR abs/2209.15618 (2022) - [i159]Matthew Aitchison, Penny Sweetser, Marcus Hutter:
Atari-5: Distilling the Arcade Learning Environment down to Five Games. CoRR abs/2210.02019 (2022) - [i158]Jörg Bornschein, Yazhe Li, Marcus Hutter:
Sequential Learning Of Neural Networks for Prequential MDL. CoRR abs/2210.07931 (2022) - [i157]Marcus Hutter:
Testing Independence of Exchangeable Random Variables. CoRR abs/2210.12392 (2022) - [i156]Tomer Galanti, András György, Marcus Hutter:
Generalization Bounds for Transfer Learning with Pretrained Classifiers. CoRR abs/2212.12532 (2022) - 2021
- [j47]Marcus Hutter:
Feature Reinforcement Learning: Part II. Structured MDPs. J. Artif. Gen. Intell. 12(1): 71-86 (2021) - [j46]Michael K. Cohen, Elliot Catt, Marcus Hutter:
Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal Agent. IEEE J. Sel. Areas Inf. Theory 2(2): 665-677 (2021) - [j45]Michael K. Cohen, Badri N. Vellambi, Marcus Hutter:
Intelligence and Unambitiousness Using Algorithmic Information Theory. IEEE J. Sel. Areas Inf. Theory 2(2): 678-690 (2021) - [j44]Tom Everitt, Marcus Hutter, Ramana Kumar, Victoria Krakovna:
Reward tampering problems and solutions in reinforcement learning: a causal influence diagram perspective. Synth. 198(27): 6435-6467 (2021) - [c116]Sultan Javed Majeed, Marcus Hutter:
Exact Reduction of Huge Action Spaces in General Reinforcement Learning. AAAI 2021: 8874-8883 - [c115]Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter:
Gated Linear Networks. AAAI 2021: 10015-10023 - [c114]Samuel Allen Alexander, Marcus Hutter:
Reward-Punishment Symmetric Universal Intelligence. AGI 2021: 1-10 - [c113]Len Du, Marcus Hutter:
How Useful are Hand-crafted Data? Making Cases for Anomaly Detection Methods. HICSS 2021: 1-10 - [c112]Thomas Mesnard, Theophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Thomas S. Stepleton, Nicolas Heess, Arthur Guez, Eric Moulines, Marcus Hutter, Lars Buesing, Rémi Munos:
Counterfactual Credit Assignment in Model-Free Reinforcement Learning. ICML 2021: 7654-7664 - [i155]Marcus Hutter:
Learning Curve Theory. CoRR abs/2102.04074 (2021) - [i154]Michael K. Cohen, Marcus Hutter, Neel Nanda:
Fully General Online Imitation Learning. CoRR abs/2102.08686 (2021) - [i153]Michael K. Cohen, Badri N. Vellambi, Marcus Hutter:
Intelligence and Unambitiousness Using Algorithmic Information Theory. CoRR abs/2105.06268 (2021) - [i152]Elliot Catt, Marcus Hutter, Joel Veness:
Reinforcement Learning with Information-Theoretic Actuation. CoRR abs/2109.15147 (2021) - [i151]Samuel Allen Alexander, Marcus Hutter:
Reward-Punishment Symmetric Universal Intelligence. CoRR abs/2110.02450 (2021) - [i150]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, Emilio Parisotto, Tom Erez, Yutian Chen, Scott E. Reed, Marcus Hutter, Nando de Freitas, Shane Legg:
Shaking the foundations: delusions in sequence models for interaction and control. CoRR abs/2110.10819 (2021) - [i149]Sultan Javed Majeed, Marcus Hutter:
Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions. CoRR abs/2112.13386 (2021) - [i148]Laurent Orseau, Marcus Hutter:
Isotuning With Applications To Scale-Free Online Learning. CoRR abs/2112.14586 (2021) - [i147]Tomer Galanti, András György, Marcus Hutter:
On the Role of Neural Collapse in Transfer Learning. CoRR abs/2112.15121 (2021) - 2020
- [c111]Michael K. Cohen, Badri N. Vellambi, Marcus Hutter:
Asymptotically Unambitious Artificial General Intelligence. AAAI 2020: 2467-2476 - [c110]Michael K. Cohen, Marcus Hutter:
Pessimism About Unknown Unknowns Inspires Conservatism. COLT 2020: 1344-1373 - [c109]Laurent Orseau, Marcus Hutter, Omar Rivasplata:
Logarithmic Pruning is All You Need. NeurIPS 2020 - [c108]Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness:
Online Learning in Contextual Bandits using Gated Linear Networks. NeurIPS 2020 - [c107]Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness:
A Combinatorial Perspective on Transfer Learning. NeurIPS 2020 - [i146]Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness:
Online Learning in Contextual Bandits using Gated Linear Networks. CoRR abs/2002.11611 (2020) - [i145]Elliot Catt, Marcus Hutter:
A Gentle Introduction to Quantum Computing Algorithms with Applications to Universal Prediction. CoRR abs/2005.03137 (2020) - [i144]Michael K. Cohen, Marcus Hutter:
Curiosity Killed the Cat and the Asymptotically Optimal Agent. CoRR abs/2006.03357 (2020) - [i143]Michael K. Cohen, Marcus Hutter:
Pessimism About Unknown Unknowns Inspires Conservatism. CoRR abs/2006.08753 (2020) - [i142]Laurent Orseau, Marcus Hutter, Omar Rivasplata:
Logarithmic Pruning is All You Need. CoRR abs/2006.12156 (2020) - [i141]Marcus Hutter:
On Representing (Anti)Symmetric Functions. CoRR abs/2007.15298 (2020) - [i140]Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness:
A Combinatorial Perspective on Transfer Learning. CoRR abs/2010.12268 (2020) - [i139]Thomas Mesnard, Théophane Weber, Fabio Viola, Shantanu Thakoor, Alaa Saade, Anna Harutyunyan, Will Dabney, Tom Stepleton, Nicolas Heess, Arthur Guez, Marcus Hutter, Lars Buesing, Rémi Munos:
Counterfactual Credit Assignment in Model-Free Reinforcement Learning. CoRR abs/2011.09464 (2020) - [i138]Sultan Javed Majeed, Marcus Hutter:
Exact Reduction of Huge Action Spaces in General Reinforcement Learning. CoRR abs/2012.10200 (2020)
2010 – 2019
- 2019
- [c106]Sultan Javed Majeed, Marcus Hutter:
Performance Guarantees for Homomorphisms beyond Markov Decision Processes. AAAI 2019: 7659-7666 - [c105]Michael K. Cohen, Elliot Catt, Marcus Hutter:
A Strongly Asymptotically Optimal Agent in General Environments. IJCAI 2019: 2179-2186 - [c104]Marcus Hutter, Samuel Yang-Zhao, Sultan Javed Majeed:
Conditions on Features for Temporal Difference-Like Methods to Converge. IJCAI 2019: 2570-2577 - [i137]Michael K. Cohen, Elliot Catt, Marcus Hutter:
Strong Asymptotic Optimality in General Environments. CoRR abs/1903.01021 (2019) - [i136]Marcus Hutter, Samuel Yang-Zhao, Sultan Javed Majeed:
Conditions on Features for Temporal Difference-Like Methods to Converge. CoRR abs/1905.11702 (2019) - [i135]Michael K. Cohen, Badri N. Vellambi, Marcus Hutter:
Asymptotically Unambitious Artificial General Intelligence. CoRR abs/1905.12186 (2019) - [i134]Marcus Hutter:
Fairness without Regret. CoRR abs/1907.05159 (2019) - [i133]Tom Everitt, Marcus Hutter:
Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective. CoRR abs/1908.04734 (2019) - [i132]Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter:
Gated Linear Networks. CoRR abs/1910.01526 (2019) - 2018
- [j43]Jan Leike, Marcus Hutter:
On the computability of Solomonoff induction and AIXI. Theor. Comput. Sci. 716: 28-49 (2018) - [j42]Marcus Hutter:
Tractability of batch to sequential conversion. Theor. Comput. Sci. 733: 71-82 (2018) - [c103]Badri N. Vellambi, Cameron Owen, Marcus Hutter:
Universal Compression of Piecewise i.i.d. Sources. DCC 2018: 267-276 - [c102]Sultan Javed Majeed, Marcus Hutter:
On Q-learning Convergence for Non-Markov Decision Processes. IJCAI 2018: 2546-2552 - [c101]Tom Everitt, Gary Lea, Marcus Hutter:
AGI Safety Literature Review. IJCAI 2018: 5441-5449 - [c100]Badri N. Vellambi, Marcus Hutter:
Convergence of Binarized Context-tree Weighting for Estimating Distributions of Stationary Sources. ISIT 2018: 731-735 - [i131]Tom Everitt, Gary Lea, Marcus Hutter:
AGI Safety Literature Review. CoRR abs/1805.01109 (2018) - [i130]Sultan Javed Majeed, Marcus Hutter:
Performance Guarantees for Homomorphisms Beyond Markov Decision Processes. CoRR abs/1811.03895 (2018) - 2017
- [c99]Tobias Wängberg, Mikael Böörs, Elliot Catt, Tom Everitt, Marcus Hutter:
A Game-Theoretic Analysis of the Off-Switch Game. AGI 2017: 167-177 - [c98]Sean Lamont, John Aslanides, Jan Leike, Marcus Hutter:
Generalised Discount Functions applied to a Monte-Carlo AI u Implementation. AAMAS 2017: 1589-1591 - [c97]John Aslanides, Jan Leike, Marcus Hutter:
Universal Reinforcement Learning Algorithms: Survey and Experiments. IJCAI 2017: 1403-1410 - [c96]Jarryd Martin, Suraj Narayanan Sasikumar, Tom Everitt, Marcus Hutter:
Count-Based Exploration in Feature Space for Reinforcement Learning. IJCAI 2017: 2471-2478 - [c95]Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter:
On Thompson Sampling and Asymptotic Optimality. IJCAI 2017: 4889-4893 - [r2]Marcus Hutter:
Universal Learning Theory. Encyclopedia of Machine Learning and Data Mining 2017: 1295-1304 - [i129]Sean Lamont, John Aslanides, Jan Leike, Marcus Hutter:
Generalised Discount Functions applied to a Monte-Carlo AImu Implementation. CoRR abs/1703.01358 (2017) - [i128]Tom Everitt, Victoria Krakovna, Laurent Orseau, Marcus Hutter, Shane Legg:
Reinforcement Learning with a Corrupted Reward Channel. CoRR abs/1705.08417 (2017) - [i127]John Aslanides, Jan Leike, Marcus Hutter:
Universal Reinforcement Learning Algorithms: Survey and Experiments. CoRR abs/1705.10557 (2017) - [i126]Jarryd Martin, Suraj Narayanan Sasikumar, Tom Everitt, Marcus Hutter:
Count-Based Exploration in Feature Space for Reinforcement Learning. CoRR abs/1706.08090 (2017) - [i125]Tobias Wängberg, Mikael Böörs, Elliot Catt, Tom Everitt, Marcus Hutter:
A Game-Theoretic Analysis of the Off-Switch Game. CoRR abs/1708.03871 (2017) - 2016
- [j41]Marcus Hutter:
Extreme state aggregation beyond Markov decision processes. Theor. Comput. Sci. 650: 73-91 (2016) - [c94]Tom Everitt, Daniel Filan, Mayank Daswani, Marcus Hutter:
Self-Modification of Policy and Utility Function in Rational Agents. AGI 2016: 1-11 - [c93]Tom Everitt, Marcus Hutter:
Avoiding Wireheading with Value Reinforcement Learning. AGI 2016: 12-22 - [c92]Jarryd Martin, Tom Everitt, Marcus Hutter:
Death and Suicide in Universal Artificial Intelligence. AGI 2016: 23-32 - [c91]Daniel Filan, Jan Leike, Marcus Hutter:
Loss Bounds and Time Complexity for Speed Priors. AISTATS 2016: 1394-1402 - [c90]Basura Fernando, Peter Anderson, Marcus Hutter, Stephen Gould:
Discriminative Hierarchical Rank Pooling for Activity Recognition. CVPR 2016: 1924-1932 - [c89]Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter:
Thompson Sampling is Asymptotically Optimal in General Environments. UAI 2016 - [i124]Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter:
Thompson Sampling is Asymptotically Optimal in General Environments. CoRR abs/1602.07905 (2016) - [i123]Daniel Filan, Marcus Hutter, Jan Leike:
Loss Bounds and Time Complexity for Speed Priors. CoRR abs/1604.03343 (2016) - [i122]Tom Everitt, Daniel Filan, Mayank Daswani, Marcus Hutter:
Self-Modification of Policy and Utility Function in Rational Agents. CoRR abs/1605.03142 (2016) - [i121]Tom Everitt, Marcus Hutter:
Avoiding Wireheading with Value Reinforcement Learning. CoRR abs/1605.03143 (2016) - [i120]Jarryd Martin, Tom Everitt, Marcus Hutter:
Death and Suicide in Universal Artificial Intelligence. CoRR abs/1606.00652 (2016) - [i119]Tom Everitt, Tor Lattimore, Marcus Hutter:
Free Lunch for Optimisation under the Universal Distribution. CoRR abs/1608.04544 (2016) - 2015
- [j40]Peter Sunehag, Marcus Hutter:
Rationality, optimism and guarantees in general reinforcement learning. J. Mach. Learn. Res. 16: 1345-1390 (2015) - [j39]Tor Lattimore, Marcus Hutter:
On Martin-Löf (non-)convergence of Solomonoff's universal mixture. Theor. Comput. Sci. 588: 2-15 (2015) - [c88]Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins:
Compress and Control. AAAI 2015: 3016-3023 - [c87]Peter Sunehag, Marcus Hutter:
Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning. AGI 2015: 177-186 - [c86]Tom Everitt, Jan Leike, Marcus Hutter:
Sequential Extensions of Causal and Evidential Decision Theory. ADT 2015: 205-221 - [c85]Jan Leike, Marcus Hutter:
Solomonoff Induction Violates Nicod's Criterion. ALT 2015: 349-363 - [c84]Jan Leike, Marcus Hutter:
On the Computability of Solomonoff Induction and Knowledge-Seeking. ALT 2015: 364-378 - [c83]Tom Everitt, Marcus Hutter:
Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search. Australasian Conference on Artificial Intelligence 2015: 157-165 - [c82]Tom Everitt, Marcus Hutter:
Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search. Australasian Conference on Artificial Intelligence 2015: 166-178 - [c81]Jan Leike, Marcus Hutter:
Bad Universal Priors and Notions of Optimality. COLT 2015: 1244-1259 - [c80]Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare:
Online Learning of k-CNF Boolean Functions. IJCAI 2015: 3865-3873 - [c79]Jan Leike, Marcus Hutter:
On the Computability of AIXI. UAI 2015: 464-473 - [i118]Tom Everitt, Jan Leike, Marcus Hutter:
Sequential Extensions of Causal and Evidential Decision Theory. CoRR abs/1506.07359 (2015) - [i117]Jan Leike, Marcus Hutter:
Solomonoff Induction Violates Nicod's Criterion. CoRR abs/1507.04121 (2015) - [i116]Jan Leike, Marcus Hutter:
On the Computability of Solomonoff Induction and Knowledge-Seeking. CoRR abs/1507.04124 (2015) - [i115]Tom Everitt, Marcus Hutter:
A Topological Approach to Meta-heuristics: Analytical Results on the BFS vs. DFS Algorithm Selection Problem. CoRR abs/1509.02709 (2015) - [i114]Jan Leike, Marcus Hutter:
Bad Universal Priors and Notions of Optimality. CoRR abs/1510.04931 (2015) - [i113]Jan Leike, Marcus Hutter:
On the Computability of AIXI. CoRR abs/1510.05572 (2015) - 2014
- [j38]Tor Lattimore, Marcus Hutter:
General time consistent discounting. Theor. Comput. Sci. 519: 140-154 (2014) - [j37]Tor Lattimore, Marcus Hutter:
Near-optimal PAC bounds for discounted MDPs. Theor. Comput. Sci. 558: 125-143 (2014) - [c78]Srimal Jayawardena, Stephen Gould, Hongdong Li, Marcus Hutter, Richard I. Hartley:
Reliable Point Correspondences in Scenes Dominated by Highly Reflective and Largely Homogeneous Surfaces. ACCV Workshops (1) 2014: 659-674 - [c77]Mayank Daswani, Peter Sunehag, Marcus Hutter:
Reinforcement learning with value advice. ACML 2014 - [c76]Peter Sunehag, Marcus Hutter:
Intelligence as Inference or Forcing Occam on the World. AGI 2014: 186-195 - [c75]Tor Lattimore, Marcus Hutter:
Bayesian Reinforcement Learning with Exploration. ALT 2014: 170-184 - [c74]Marcus Hutter:
Extreme State Aggregation beyond MDPs. ALT 2014: 185-199 - [c73]