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2020 – today
- 2025
[i181]Li Kevin Wenliang, Anian Ruoss, Jordi Grau-Moya, Marcus Hutter, Tim Genewein:
Why is prompting hard? Understanding prompts on binary sequence predictors. CoRR abs/2502.10760 (2025)- [i180]Joel Veness, Marcus Hutter, András György, Jordi Grau-Moya:
Partition Tree Weighting for Non-Stationary Stochastic Bandits. CoRR abs/2502.19325 (2025) - 2024
- [j50]Aram Ebtekar
, Marcus Hutter:
Modeling the Arrows of Time with Causal Multibaker Maps. Entropy 26(9): 776 (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 - [i179]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) - [i178]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) - [i177]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) - [i176]Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell:
RL, but don't do anything I wouldn't do. CoRR abs/2410.06213 (2024) - [i175]Laurent Orseau, Marcus Hutter, Levi H. S. Lelis:
Exponential Speedups by Rerooting Levin Tree Search. CoRR abs/2412.05196 (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) - no results
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]Marcus Hutter:
Offline to Online Conversion. ALT 2014: 230-244 - [c72]Jan Leike, Marcus Hutter:
Indefinitely Oscillating Martingales. ALT 2014: 321-335 - [c71]Tom Everitt, Tor Lattimore, Marcus Hutter:
Free Lunch for optimisation under the universal distribution. IEEE Congress on Evolutionary Computation 2014: 167-174 - [c70]Peter Sunehag, Marcus Hutter:
A Dual Process Theory of Optimistic Cognition. CogSci 2014 - [c69]Di Yang, Srimal Jayawardena, Stephen Gould, Marcus Hutter:
Reflective Features Detection and Hierarchical Reflections Separation in Image Sequences. DICTA 2014: 1-7 - [c68]Tansu Alpcan, Tom Everitt, Marcus Hutter:
Can we measure the difficulty of an optimization problem? ITW 2014: 356-360 - [i112]Joel Veness, Marcus Hutter:
Online Learning of k-CNF Boolean Functions. CoRR abs/1403.6863 (2014) - [i111]Marcus Hutter:
Offline to Online Conversion. CoRR abs/1407.3334 (2014) - [i110]Marcus Hutter:
Extreme State Aggregation Beyond MDPs. CoRR abs/1407.3341 (2014) - [i109]Marco Zaffalon, Marcus Hutter:
Robust Feature Selection by Mutual Information Distributions. CoRR abs/1408.1487 (2014) - [i108]Jan Leike, Marcus Hutter:
Indefinitely Oscillating Martingales. CoRR abs/1408.3169 (2014) - [i107]Tor Lattimore, Marcus Hutter:
Asymptotics of Continuous Bayes for Non-i.i.d. Sources. CoRR abs/1411.2918 (2014) - [i106]Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins:
Compress and Control. CoRR abs/1411.5326 (2014) - 2013
- [j36]Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther:
Probabilities on Sentences in an Expressive Logic. J. Appl. Log. 11(4): 386-420 (2013) - [j35]Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann:
Guest Editors' foreword. Theor. Comput. Sci. 473: 1-3 (2013) - [c67]Mayank Daswani, Peter Sunehag, Marcus Hutter:
Q-learning for history-based reinforcement learning. ACML 2013: 213-228 - [c66]Peter Sunehag, Marcus Hutter:
Learning Agents with Evolving Hypothesis Classes. AGI 2013: 150-159 - [c65]Laurent Orseau, Tor Lattimore, Marcus Hutter:
Universal Knowledge-Seeking Agents for Stochastic Environments. ALT 2013: 158-172 - [c64]Tor Lattimore, Marcus Hutter, Peter Sunehag:
Concentration and Confidence for Discrete Bayesian Sequence Predictors. ALT 2013: 324-338 - [c63]Marcus Hutter:
Sparse Adaptive Dirichlet-Multinomial-like Processes. COLT 2013: 432-459 - [c62]Tor Lattimore, Marcus Hutter, Peter Sunehag:
The Sample-Complexity of General Reinforcement Learning. ICML (3) 2013: 28-36 - [c61]Tor Lattimore, Marcus Hutter:
On Martin-Löf Convergence of Solomonoff's Mixture. TAMC 2013: 212-223 - [i105]Marcus Hutter:
Sparse Adaptive Dirichlet-Multinomial-like Processes. CoRR abs/1305.3671 (2013) - [i104]Tor Lattimore, Marcus Hutter, Peter Sunehag:
Concentration and Confidence for Discrete Bayesian Sequence Predictors. CoRR abs/1307.0127 (2013) - [i103]Tor Lattimore, Marcus Hutter, Peter Sunehag:
The Sample-Complexity of General Reinforcement Learning. CoRR abs/1308.4828 (2013) - [i102]Srimal Jayawardena, Marcus Hutter, Nathan Brewer:
A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation. CoRR abs/1311.7186 (2013) - [i101]Peter Auer, Marcus Hutter, Laurent Orseau:
Reinforcement Learning (Dagstuhl Seminar 13321). Dagstuhl Reports 3(8): 1-26 (2013) - 2012
- [c60]Phuong Minh Nguyen, Peter Sunehag, Marcus Hutter:
Context Tree Maximizing. AAAI 2012: 1075-1082 - [c59]Di Yang, Stephen Gould, Marcus Hutter:
A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation. ACCV (1) 2012: 775-789 - [c58]Peter Sunehag, Marcus Hutter:
Optimistic AIXI. AGI 2012: 312-321 - [c57]Joel Veness, Peter Sunehag, Marcus Hutter:
On Ensemble Techniques for AIXI Approximation. AGI 2012: 341-351 - [c56]Tor Lattimore, Marcus Hutter:
PAC Bounds for Discounted MDPs. ALT 2012: 320-334 - [c55]Peter Sunehag, Marcus Hutter:
Optimistic Agents Are Asymptotically Optimal. Australasian Conference on Artificial Intelligence 2012: 15-26 - [c54]Peter Sunehag, Wen Shao, Marcus Hutter:
Coding of Non-Stationary Sources as a Foundation for Detecting Change Points and Outliers in Binary Time-Series. AusDM 2012: 79-84 - [c53]Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag:
Adaptive Context Tree Weighting. DCC 2012: 317-326 - [c52]Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling:
Context Tree Switching. DCC 2012: 327-336 - [c51]Mayank Daswani, Peter Sunehag, Marcus Hutter:
Feature Reinforcement Learning using Looping Suffix Trees. EWRL 2012: 11-24 - [e4]Scott Sanner, Marcus Hutter:
Recent Advances in Reinforcement Learning - 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised Selected Papers. Lecture Notes in Computer Science 7188, Springer 2012, ISBN 978-3-642-29945-2 [contents] - [i100]Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag:
Adaptive Context Tree Weighting. CoRR abs/1201.2056 (2012) - [i99]Srimal Jayawardena, Di Yang, Marcus Hutter:
3D Model Assisted Image Segmentation. CoRR abs/1202.1943 (2012) - [i98]Tor Lattimore, Marcus Hutter:
PAC Bounds for Discounted MDPs. CoRR abs/1202.3890 (2012) - [i97]Marcus Hutter:
One Decade of Universal Artificial Intelligence. CoRR abs/1202.6153 (2012) - [i96]Marcus Hutter:
Can Intelligence Explode? CoRR abs/1202.6177 (2012) - [i95]Joel Veness, Marcus Hutter:
Sparse Sequential Dirichlet Coding. CoRR abs/1206.3618 (2012) - [i94]Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther:
Probabilities on Sentences in an Expressive Logic. CoRR abs/1209.2620 (2012) - [i93]Peter Sunehag, Marcus Hutter:
Optimistic Agents are Asymptotically Optimal. CoRR abs/1210.0077 (2012) - 2011
- [j34]Samuel Rathmanner, Marcus Hutter:
A Philosophical Treatise of Universal Induction. Entropy 13(6): 1076-1136 (2011) - [j33]Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver:
A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. 40: 95-142 (2011) - [c50]Tor Lattimore, Marcus Hutter, Vaibhav Gavane:
Universal Prediction of Selected Bits. ALT 2011: 262-276 - [c49]Peter Sunehag, Marcus Hutter:
Axioms for Rational Reinforcement Learning. ALT 2011: 338-352 - [c48]Tor Lattimore, Marcus Hutter:
Asymptotically Optimal Agents. ALT 2011: 368-382 - [c47]Tor Lattimore, Marcus Hutter:
Time Consistent Discounting. ALT 2011: 383-397 - [c46]Tor Lattimore, Marcus Hutter:
No Free Lunch versus Occam's Razor in Supervised Learning. Algorithmic Probability and Friends 2011: 223-235 - [c45]Peter Sunehag, Marcus Hutter:
Principles of Solomonoff Induction and AIXI. Algorithmic Probability and Friends 2011: 386-398 - [c44]Ian Wood, Peter Sunehag, Marcus Hutter:
(Non-)Equivalence of Universal Priors. Algorithmic Probability and Friends 2011: 417-425 - [c43]Srimal Jayawardena, Marcus Hutter, Nathan Brewer:
A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation. DICTA 2011: 37-44 - [c42]Srimal Jayawardena, Di Yang, Marcus Hutter:
3D Model Assisted Image Segmentation. DICTA 2011: 51-58 - [c41]Phuong Minh Nguyen, Peter Sunehag, Marcus Hutter:
Feature Reinforcement Learning in Practice. EWRL 2011: 66-77 - [i92]Marcus Hutter:
Universal Learning Theory. CoRR abs/1102.2467 (2011) - [i91]Marcus Hutter:
Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence. CoRR abs/1102.2468 (2011) - [i90]Samuel Rathmanner, Marcus Hutter:
A Philosophical Treatise of Universal Induction. CoRR abs/1105.5721 (2011) - [i89]Peter Sunehag, Marcus Hutter:
Axioms for Rational Reinforcement Learning. CoRR abs/1107.5520 (2011) - [i88]Tor Lattimore, Marcus Hutter:
Time Consistent Discounting. CoRR abs/1107.5528 (2011) - [i87]Tor Lattimore, Marcus Hutter, Vaibhav Gavane:
Universal Prediction of Selected Bits. CoRR abs/1107.5531 (2011) - [i86]Tor Lattimore, Marcus Hutter:
Asymptotically Optimal Agents. CoRR abs/1107.5537 (2011) - [i85]Phuong Minh Nguyen, Peter Sunehag, Marcus Hutter:
Feature Reinforcement Learning In Practice. CoRR abs/1108.3614 (2011) - [i84]Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling:
Context Tree Switching. CoRR abs/1111.3182 (2011) - [i83]Tor Lattimore, Marcus Hutter:
No Free Lunch versus Occam's Razor in Supervised Learning. CoRR abs/1111.3846 (2011) - [i82]Ian Wood, Peter Sunehag, Marcus Hutter:
(Non-)Equivalence of Universal Priors. CoRR abs/1111.3854 (2011) - [i81]Peter Sunehag, Marcus Hutter:
Principles of Solomonoff Induction and AIXI. CoRR abs/1111.6117 (2011) - 2010
- [j32]Ben Goertzel, Marcus Hutter:
Report on the Third Conference on Artificial General Intelligence. AI Mag. 31(3): 123-124 (2010) - [j31]Marcus Hutter:
A Complete Theory of Everything (Will Be Subjective). Algorithms 3(4): 329-350 (2010) - [j30]Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee:
An integrated Bayesian analysis of LOH and copy number data. BMC Bioinform. 11: 321 (2010) - [j29]Marcus Hutter, Minh-Ngoc Tran:
Model selection with the Loss Rank Principle. Comput. Stat. Data Anal. 54(5): 1288-1306 (2010) - [c40]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
Reinforcement Learning via AIXI Approximation. AAAI 2010: 605-611 - [c39]Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann:
Editors' Introduction. ALT 2010: 1-10 - [c38]Peter Sunehag, Marcus Hutter:
Consistency of Feature Markov Processes. ALT 2010: 360-374 - [e3]Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann:
Algorithmic Learning Theory, 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings. Lecture Notes in Computer Science 6331, Springer 2010, ISBN 978-3-642-16107-0 [contents] - [r1]Marcus Hutter:
Universal Learning Theory. Encyclopedia of Machine Learning 2010: 1001-1008 - [i80]Marcus Hutter, Minh-Ngoc Tran:
Model Selection with the Loss Rank Principle. CoRR abs/1003.0516 (2010) - [i79]Wray L. Buntine, Marcus Hutter:
A Bayesian Review of the Poisson-Dirichlet Process. CoRR abs/1007.0296 (2010) - [i78]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
Reinforcement Learning via AIXI Approximation. CoRR abs/1007.2049 (2010) - [i77]Peter Sunehag, Marcus Hutter:
Consistency of Feature Markov Processes. CoRR abs/1007.2075 (2010) - [i76]Srimal Jayawardena, Marcus Hutter, Nathan Brewer:
Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss. CoRR abs/1011.1035 (2010) - no results
2000 – 2009
- 2009
- [j28]Marcus Hutter:
Open Problems in Universal Induction & Intelligence. Algorithms 2(3): 879-906 (2009) - [j27]Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee:
Bayesian DNA copy number analysis. BMC Bioinform. 10 (2009) - [j26]Marcus Hutter:
Practical robust estimators for the imprecise Dirichlet model. Int. J. Approx. Reason. 50(2): 231-242 (2009) - [j25]Alberto Piatti, Marco Zaffalon, Fabio Trojani, Marcus Hutter:
Limits of learning about a categorical latent variable under prior near-ignorance. Int. J. Approx. Reason. 50(4): 597-611 (2009) - [j24]Marcus Hutter:
Feature Reinforcement Learning: Part I. Unstructured MDPs. J. Artif. Gen. Intell. 1(1): 3-24 (2009) - [j23]Marcus Hutter, Rocco A. Servedio:
Preface. Theor. Comput. Sci. 410(19): 1747-1748 (2009) - [c37]Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee:
Bayesian Joint Estimation of CN and LOH Aberrations. IWANN (2) 2009: 1109-1117 - [c36]Marcus Hutter:
Discrete MDL Predicts in Total Variation. NIPS 2009: 817-825 - [c35]Ke Zhang, Marcus Hutter, Huidong Jin:
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data. PAKDD 2009: 813-822 - [i75]Marcus Hutter:
Practical Robust Estimators for the Imprecise Dirichlet Model. CoRR abs/0901.4137 (2009) - [i74]Ke Zhang, Marcus Hutter, Huidong Jin:
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data. CoRR abs/0903.3257 (2009) - [i73]Marcus Hutter:
Exact Non-Parametric Bayesian Inference on Infinite Trees. CoRR abs/0903.5342 (2009) - [i72]Alberto Piatti, Marco Zaffalon, Fabio Trojani, Marcus Hutter:
Limits of Learning about a Categorical Latent Variable under Prior Near-Ignorance. CoRR abs/0904.4527 (2009) - [i71]Marcus Hutter:
Feature Reinforcement Learning: Part I: Unstructured MDPs. CoRR abs/0906.1713 (2009) - [i70]Marcus Hutter:
Open Problems in Universal Induction & Intelligence. CoRR abs/0907.0746 (2009) - [i69]Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver:
A Monte Carlo AIXI Approximation. CoRR abs/0909.0801 (2009) - [i68]Marcus Hutter:
Discrete MDL Predicts in Total Variation. CoRR abs/0909.4588 (2009) - [i67]Marcus Hutter, Nathan Brewer:
Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation. CoRR abs/0912.3589 (2009) - [i66]Marcus Hutter:
A Complete Theory of Everything (will be subjective). CoRR abs/0912.5434 (2009) - 2008
- [j22]Daniil Ryabko, Marcus Hutter:
Predicting non-stationary processes. Appl. Math. Lett. 21(5): 477-482 (2008) - [j21]Marcus Hutter:
Algorithmic complexity. Scholarpedia 3(1): 2573 (2008) - [j20]Daniil Ryabko, Marcus Hutter:
On the possibility of learning in reactive environments with arbitrary dependence. Theor. Comput. Sci. 405(3): 274-284 (2008) - [c34]Kassel Hingee, Marcus Hutter:
Equivalence of probabilistic tournament and polynomial ranking selection. IEEE Congress on Evolutionary Computation 2008: 564-571 - [i65]Kassel Hingee, Marcus Hutter:
Equivalence of Probabilistic Tournament and Polynomial Ranking Selection. CoRR abs/0803.2925 (2008) - [i64]Marcus Hutter:
Predictive Hypothesis Identification. CoRR abs/0809.1270 (2008) - [i63]Marcus Hutter, Shane Legg:
Temporal Difference Updating without a Learning Rate. CoRR abs/0810.5631 (2008) - [i62]Daniil Ryabko, Marcus Hutter:
On the Possibility of Learning in Reactive Environments with Arbitrary Dependence. CoRR abs/0810.5636 (2008) - [i61]Marcus Hutter:
Feature Markov Decision Processes. CoRR abs/0812.4580 (2008) - [i60]Marcus Hutter:
Feature Dynamic Bayesian Networks. CoRR abs/0812.4581 (2008) - 2007
- [j19]Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber:
Algorithmic complexity bounds on future prediction errors. Inf. Comput. 205(2): 242-261 (2007) - [j18]Shane Legg, Marcus Hutter:
Universal Intelligence: A Definition of Machine Intelligence. Minds Mach. 17(4): 391-444 (2007) - [j17]Marcus Hutter:
Algorithmic information theory. Scholarpedia 2(3): 2519 (2007) - [j16]Marcus Hutter, Shane Legg, Paul M. B. Vitányi:
Algorithmic probability. Scholarpedia 2(8): 2572 (2007) - [j15]Marcus Hutter, Andrej Muchnik:
On semimeasures predicting Martin-Löf random sequences. Theor. Comput. Sci. 382(3): 247-261 (2007) - [j14]Marcus Hutter:
On universal prediction and Bayesian confirmation. Theor. Comput. Sci. 384(1): 33-48 (2007) - [c33]Marcus Hutter, Rocco A. Servedio, Eiji Takimoto:
Editors' Introduction. ALT 2007: 1-8 - [c32]Marcus Hutter:
The Loss Rank Principle for Model Selection. COLT 2007: 589-603 - [c31]Daniil Ryabko, Marcus Hutter:
On Sequence Prediction for Arbitrary Measures. ISIT 2007: 2346-2350 - [c30]Marcus Hutter, Shane Legg:
Temporal Difference Updating without a Learning Rate. NIPS 2007: 705-712 - [p1]Marcus Hutter:
Universal Algorithmic Intelligence: A Mathematical Top→Down Approach. Artificial General Intelligence 2007: 227-290 - [e2]Marcus Hutter, Rocco A. Servedio, Eiji Takimoto:
Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings. Lecture Notes in Computer Science 4754, Springer 2007, ISBN 978-3-540-75224-0 [contents] - [i59]Shane Legg, Marcus Hutter:
A Collection of Definitions of Intelligence. CoRR abs/0706.3639 (2007) - [i58]Marcus Hutter, Andrej Muchnik:
On Semimeasures Predicting Martin-Loef Random Sequences. CoRR abs/0708.2319 (2007) - [i57]Marcus Hutter:
On Universal Prediction and Bayesian Confirmation. CoRR abs/0709.1516 (2007) - [i56]Shane Legg, Marcus Hutter:
Universal Intelligence: A Definition of Machine Intelligence. CoRR abs/0712.3329 (2007) - [i55]Shane Legg, Marcus Hutter:
Tests of Machine Intelligence. CoRR abs/0712.3825 (2007) - [i54]Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber:
Algorithmic Complexity Bounds on Future Prediction Errors. CoRR abs/cs/0701120 (2007) - [i53]Marcus Hutter:
Universal Algorithmic Intelligence: A mathematical top->down approach. CoRR abs/cs/0701125 (2007) - [i52]Marcus Hutter:
Algorithmic Information Theory: a brief non-technical guide to the field. CoRR abs/cs/0703024 (2007) - [i51]Marcus Hutter:
The Loss Rank Principle for Model Selection. CoRR abs/math/0702804 (2007) - 2006
- [j13]Monaldo Mastrolilli, Marcus Hutter:
Hybrid rounding techniques for knapsack problems. Discret. Appl. Math. 154(4): 640-649 (2006) - [j12]Marcus Hutter:
Sequential predictions based on algorithmic complexity. J. Comput. Syst. Sci. 72(1): 95-117 (2006) - [j11]Jan Poland, Marcus Hutter:
MDL convergence speed for Bernoulli sequences. Stat. Comput. 16(2): 161-175 (2006) - [j10]Marcus Hutter:
On generalized computable universal priors and their convergence. Theor. Comput. Sci. 364(1): 27-41 (2006) - [j9]Marcus Hutter, Shane Legg:
Fitness uniform optimization. IEEE Trans. Evol. Comput. 10(5): 568-589 (2006) - [c29]Shane Legg, Marcus Hutter:
A Collection of Definitions of Intelligence. AGI 2006: 17-24 - [c28]Shane Legg, Marcus Hutter:
Tests of Machine Intelligence. 50 Years of Artificial Intelligence 2006: 232-242 - [c27]Marcus Hutter:
General Discounting Versus Average Reward. ALT 2006: 244-258 - [c26]Daniil Ryabko, Marcus Hutter:
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence. ALT 2006: 334-347 - [c25]Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber:
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot. IAS 2006: 272-281 - [c24]Marcus Hutter:
On the Foundations of Universal Sequence Prediction. TAMC 2006: 408-420 - [e1]Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi:
Kolmogorov Complexity and Applications, 29.01. - 03.02.2006. Dagstuhl Seminar Proceedings 06051, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2006 [contents] - [i50]Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber:
Complexity Monotone in Conditions and Future Prediction Errors. Kolmogorov Complexity and Applications 2006 - [i49]Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi:
06051 Abstracts Collection -- Kolmogorov Complexity and Applications. Kolmogorov Complexity and Applications 2006 - [i48]Daniil Ryabko, Marcus Hutter:
Sequence prediction for non-stationary processes. Combinatorial and Algorithmic Foundations of Pattern and Association Discovery 2006 - [i47]Daniil Ryabko, Marcus Hutter:
Learning in Reactive Environments with Arbitrary Dependence. Kolmogorov Complexity and Applications 2006 - [i46]Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber:
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot. CoRR abs/cs/0603023 (2006) - [i45]Daniil Ryabko, Marcus Hutter:
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence. CoRR abs/cs/0603110 (2006) - [i44]Marcus Hutter:
On the Foundations of Universal Sequence Prediction. CoRR abs/cs/0605009 (2006) - [i43]Shane Legg, Marcus Hutter:
A Formal Measure of Machine Intelligence. CoRR abs/cs/0605024 (2006) - [i42]Marcus Hutter:
General Discounting versus Average Reward. CoRR abs/cs/0605040 (2006) - [i41]Daniil Ryabko, Marcus Hutter:
On Sequence Prediction for Arbitrary Measures. CoRR abs/cs/0606077 (2006) - [i40]Marcus Hutter, Shane Legg:
Fitness Uniform Optimization. CoRR abs/cs/0610126 (2006) - [i39]Jan Poland, Marcus Hutter:
MDL Convergence Speed for Bernoulli Sequences. CoRR abs/math/0602505 (2006) - [i38]Marcus Hutter:
Bayesian Regression of Piecewise Constant Functions. CoRR abs/math/0606315 (2006) - 2005
- [b1]Marcus Hutter:
Universal Artificial Intellegence - Sequential Decisions Based on Algorithmic Probability. Texts in Theoretical Computer Science. An EATCS Series, Springer 2005, ISBN 978-3-540-22139-5, pp. 1-280 - [j8]Marco Zaffalon, Marcus Hutter:
Robust inference of trees. Ann. Math. Artif. Intell. 45(1-2): 215-239 (2005) - [j7]Marcus Hutter, Marco Zaffalon:
Distribution of mutual information from complete and incomplete data. Comput. Stat. Data Anal. 48(3): 633-657 (2005) - [j6]Marcus Hutter, Jan Poland:
Adaptive Online Prediction by Following the Perturbed Leader. J. Mach. Learn. Res. 6: 639-660 (2005) - [j5]Jan Poland, Marcus Hutter:
Asymptotics of discrete MDL for online prediction. IEEE Trans. Inf. Theory 51(11): 3780-3795 (2005) - [c23]Marcus Hutter:
Fast Non-Parametric Bayesian Inference on Infinite Trees. AISTATS 2005: 144-151 - [c22]Jan Poland, Marcus Hutter:
Defensive Universal Learning with Experts. ALT 2005: 356-370 - [c21]Alexey V. Chernov, Marcus Hutter:
Monotone Conditional Complexity Bounds on Future Prediction Errors. ALT 2005: 414-428 - [c20]Shane Legg, Marcus Hutter:
Fitness uniform deletion: a simple way to preserve diversity. GECCO 2005: 1271-1278 - [c19]Shane Legg, Marcus Hutter:
A Universal Measure of Intelligence for Artificial Agents. IJCAI 2005: 1509-1510 - [i37]Jan Poland, Marcus Hutter:
Master Algorithms for Active Experts Problems based on Increasing Loss Values. CoRR abs/cs/0502067 (2005) - [i36]Marcus Hutter:
On Generalized Computable Universal Priors and their Convergence. CoRR abs/cs/0503026 (2005) - [i35]Shane Legg, Marcus Hutter:
Fitness Uniform Deletion: A Simple Way to Preserve Diversity. CoRR abs/cs/0504035 (2005) - [i34]Marcus Hutter, Jan Poland:
Adaptive Online Prediction by Following the Perturbed Leader. CoRR abs/cs/0504078 (2005) - [i33]Jan Poland, Marcus Hutter:
Asymptotics of Discrete MDL for Online Prediction. CoRR abs/cs/0506022 (2005) - [i32]Alexey V. Chernov, Marcus Hutter:
Monotone Conditional Complexity Bounds on Future Prediction Errors. CoRR abs/cs/0507041 (2005) - [i31]Jan Poland, Marcus Hutter:
Defensive Universal Learning with Experts. CoRR abs/cs/0507044 (2005) - [i30]Marcus Hutter:
Sequential Predictions based on Algorithmic Complexity. CoRR abs/cs/0508043 (2005) - [i29]Jan Poland, Marcus Hutter:
Universal Learning of Repeated Matrix Games. CoRR abs/cs/0508073 (2005) - [i28]Marco Zaffalon, Marcus Hutter:
Robust Inference of Trees. CoRR abs/cs/0511087 (2005) - [i27]Jan Poland, Marcus Hutter:
Strong Asymptotic Assertions for Discrete MDL in Regression and Classification. CoRR abs/math/0502315 (2005) - 2004
- [c18]Marcus Hutter, Andrej Muchnik:
Universal Convergence of Semimeasures on Individual Random Sequences. ALT 2004: 234-248 - [c17]Marcus Hutter, Jan Poland:
Prediction with Expert Advice by Following the Perturbed Leader for General Weights. ALT 2004: 279-293 - [c16]Jan Poland, Marcus Hutter:
On the Convergence Speed of MDL Predictions for Bernoulli Sequences. ALT 2004: 294-308 - [c15]Shane Legg, Marcus Hutter, Akshat Kumar:
Tournament versus fitness uniform selection. IEEE Congress on Evolutionary Computation 2004: 2144-2151 - [c14]Jan Poland, Marcus Hutter:
Convergence of Discrete MDL for Sequential Prediction. COLT 2004: 300-314 - [i26]Marcus Hutter, Marco Zaffalon:
Distribution of Mutual Information from Complete and Incomplete Data. CoRR cs.LG/0403025 (2004) - [i25]Shane Legg, Marcus Hutter, Akshat Kumar:
Tournament versus Fitness Uniform Selection. CoRR cs.LG/0403038 (2004) - [i24]Jan Poland, Marcus Hutter:
Convergence of Discrete MDL for Sequential Prediction. CoRR cs.LG/0404057 (2004) - [i23]Marcus Hutter, Jan Poland:
Prediction with Expert Advice by Following the Perturbed Leader for General Weights. CoRR cs.LG/0405043 (2004) - [i22]Jan Poland, Marcus Hutter:
On the Convergence Speed of MDL Predictions for Bernoulli Sequences. CoRR cs.LG/0407039 (2004) - [i21]Marcus Hutter, Andrej Muchnik:
Universal Convergence of Semimeasures on Individual Random Sequences. CoRR cs.LG/0407057 (2004) - 2003
- [j4]Marcus Hutter:
Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet. J. Mach. Learn. Res. 4: 971-1000 (2003) - [j3]Marcus Hutter:
Convergence and loss bounds for Bayesian sequence prediction. IEEE Trans. Inf. Theory 49(8): 2061-2067 (2003) - [c13]Marcus Hutter:
On the Existence and Convergence of Computable Universal Priors. ALT 2003: 298-312 - [c12]Marcus Hutter:
Sequence Prediction Based on Monotone Complexity. COLT 2003: 506-521 - [c11]Marcus Hutter:
An Open Problem Regarding the Convergence of Universal A Priori Probability. COLT 2003: 738-740 - [c10]Marcus Hutter:
Robust Estimators under the Imprecise Dirichlet Model. ISIPTA 2003: 274-289 - [c9]Marcus Hutter, Marco Zaffalon:
Bayesian Treatment of Incomplete Discrete Data Applied to Mutual Information and Feature Selection. KI 2003: 396-406 - [i20]Marcus Hutter:
Sequence Prediction based on Monotone Complexity. CoRR cs.AI/0306036 (2003) - [i19]Marcus Hutter:
Optimal Sequential Decisions based on Algorithmic Probability. CoRR cs.AI/0306091 (2003) - [i18]Monaldo Mastrolilli, Marcus Hutter:
Hybrid Rounding Techniques for Knapsack Problems. CoRR cs.CC/0305002 (2003) - [i17]Marcus Hutter:
Convergence and Loss Bounds for Bayesian Sequence Prediction. CoRR cs.LG/0301014 (2003) - [i16]Marcus Hutter:
On the Existence and Convergence Computable Universal Priors. CoRR cs.LG/0305052 (2003) - [i15]Marcus Hutter, Marco Zaffalon:
Bayesian Treatment of Incomplete Discrete Data applied to Mutual Information and Feature Selection. CoRR cs.LG/0306126 (2003) - [i14]Marcus Hutter:
Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet. CoRR cs.LG/0311014 (2003) - 2002
- [j2]Marcus Hutter:
The Fastest and Shortest Algorithm for all Well-Defined Problems. Int. J. Found. Comput. Sci. 13(3): 431-443 (2002) - [c8]Marcus Hutter:
Fitness uniform selection to preserve genetic diversity. IEEE Congress on Evolutionary Computation 2002: 783-788 - [c7]Marcus Hutter:
Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures. COLT 2002: 364-379 - [c6]Marco Zaffalon, Marcus Hutter:
Robust Feature Selection by Mutual Information Distributions. UAI 2002: 577-584 - [i13]Marcus Hutter:
Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures. CoRR cs.AI/0204040 (2002) - [i12]Marco Zaffalon, Marcus Hutter:
Robust Feature Selection by Mutual Information Distributions. CoRR cs.AI/0206006 (2002) - [i11]Marcus Hutter:
The Fastest and Shortest Algorithm for All Well-Defined Problems. CoRR cs.CC/0206022 (2002) - 2001
- [j1]Marcus Hutter:
New Error Bounds for Solomonoff Prediction. J. Comput. Syst. Sci. 62(4): 653-667 (2001) - [c5]Marcus Hutter:
Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions. ECML 2001: 226-238 - [c4]Marcus Hutter:
Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences. ECML 2001: 239-250 - [c3]Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber:
Market-Based Reinforcement Learning in Partially Observable Worlds. ICANN 2001: 865-873 - [c2]Marcus Hutter:
General Loss Bounds for Universal Sequence Prediction. ICML 2001: 210-217 - [c1]Marcus Hutter:
Distribution of Mutual Information. NIPS 2001: 399-406 - [i10]Marcus Hutter:
General Loss Bounds for Universal Sequence Prediction. CoRR cs.AI/0101019 (2001) - [i9]Marcus Hutter:
Fitness Uniform Selection to Preserve Genetic Diversity. CoRR cs.AI/0103015 (2001) - [i8]Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber:
Market-Based Reinforcement Learning in Partially Observable Worlds. CoRR cs.AI/0105025 (2001) - [i7]Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber:
Gradient-based Reinforcement Planning in Policy-Search Methods. CoRR cs.AI/0111060 (2001) - [i6]Marcus Hutter:
Distribution of Mutual Information. CoRR cs.AI/0112019 (2001) - [i5]Marcus Hutter:
An effective Procedure for Speeding up Algorithms. CoRR cs.CC/0102018 (2001) - [i4]Marcus Hutter:
Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences. CoRR cs.LG/0106036 (2001) - 2000
- [i3]Marcus Hutter:
A Theory of Universal Artificial Intelligence based on Algorithmic Complexity. CoRR cs.AI/0004001 (2000) - [i2]Marcus Hutter:
Towards a Universal Theory of Artificial Intelligence based on Algorithmic Probability and Sequential Decision Theory. CoRR cs.AI/0012011 (2000) - no results
1990 – 1999
- 1999
- [i1]Marcus Hutter:
New Error Bounds for Solomonoff Prediction. CoRR cs.AI/9912008 (1999) - no results
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