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ORCIDMarcus Hutter
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- affiliation: DeepMind, UK
- affiliation (former): Australian National University, Canberra, Australia
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2020 – today
- 2024
[c130]Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter:
Dynamic Knowledge Injection for AIXI Agents. AAAI 2024: 16388-16397- [c129]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 - [c128]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 - [c127]Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland:
Distributional Bellman Operators over Mean Embeddings. ICML 2024 - [i177]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) - [i176]Amal Rannen-Triki, Jörg Bornschein, Razvan Pascanu, Marcus Hutter, András György, Alexandre Galashov, Yee Whye Teh, Michalis K. Titsias:
Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models. CoRR abs/2403.01518 (2024) - [i175]Mary Phuong, Matthew Aitchison, Elliot Catt, Sarah Cogan, Alexandre Kaskasoli, Victoria Krakovna, David Lindner, Matthew Rahtz, Yannis Assael, Sarah Hodkinson, Heidi Howard, Tom Lieberum, Ramana Kumar, Maria Abi Raad, Albert Webson, Lewis Ho, Sharon Lin, Sebastian Farquhar, Marcus Hutter, Grégoire Delétang, Anian Ruoss, Seliem El-Sayed, Sasha Brown, Anca D. Dragan, Rohin Shah, Allan Dafoe, Toby Shevlane:
Evaluating Frontier Models for Dangerous Capabilities. CoRR abs/2403.13793 (2024) - 2023
- [c126]Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter:
Universal Agent Mixtures and the Geometry of Intelligence. AISTATS 2023: 4231-4246 - [c125]Jörg Bornschein, Yazhe Li, Marcus Hutter:
Sequential Learning of Neural Networks for Prequential MDL. ICLR 2023 - [c124]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 - [c123]Yazhe Li, Jörg Bornschein, Marcus Hutter:
Evaluating Representations with Readout Model Switching. ICLR 2023 - [c122]Matthew Aitchison, Penny Sweetser, Marcus Hutter:
Atari-5: Distilling the Arcade Learning Environment down to Five Games. ICML 2023: 421-438 - [c121]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 - [c120]Laurent Orseau, Marcus Hutter, Levi H. S. Lelis:
Levin Tree Search with Context Models. IJCAI 2023: 5622-5630 - [c119]Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness:
Self-Predictive Universal AI. NeurIPS 2023 - [i174]Bryn Elesedy, Marcus Hutter:
U-Clip: On-Average Unbiased Stochastic Gradient Clipping. CoRR abs/2302.02971 (2023) - [i173]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) - [i172]Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter:
Universal Agent Mixtures and the Geometry of Intelligence. CoRR abs/2302.06083 (2023) - [i171]Yazhe Li, Jörg Bornschein, Marcus Hutter:
Evaluating Representations with Readout Model Switching. CoRR abs/2302.09579 (2023) - [i170]Laurent Orseau, Marcus Hutter, Levi H. S. Lelis:
Levin Tree Search with Context Models. CoRR abs/2305.16945 (2023) - [i169]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) - [i168]Laurent Orseau, Marcus Hutter:
Line Search for Convex Minimization. CoRR abs/2307.16560 (2023) - [i167]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) - [i166]Boumediene Hamzi, Marcus Hutter, Houman Owhadi:
Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning. CoRR abs/2311.12624 (2023) - [i165]Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland:
Distributional Bellman Operators over Mean Embeddings. CoRR abs/2312.07358 (2023) - [i164]Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter:
Dynamic Knowledge Injection for AIXI Agents. CoRR abs/2312.16184 (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]