Marcus Hutter - RankMe

381 papers A* 42A 9B 38C 6Misc 5Journal 237Unranked 38

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Simplicity and Complexity in Combinatorial Optimization. Entropy Kamaludin Dingle, Marcus Hutter
2026	J	`jnl`	Time Series Correlations and Kolmogorov Complexity: A Hausdorff Dimension Perspective. CoRR Boumediene Hamzi, Marianne Clausel, Kamal Dingle, Marcus Hutter, Mohammed Terry-Jack
2025	J	`jnl`	Embedded Universal Predictive Intelligence: a coherent framework for multi-agent learning. CoRR Alexander Meulemans, Rajai Nasser, Maciej Wolczyk, Marissa A. Weis, Seijin Kobayashi, Blake A. Richards, Guillaume Lajoie, Angelika Steger, Marcus Hutter, James Manyika, Rif A. Saurous, João Sacramento, Blaise Agüera y Arcas
2025	J	`jnl`	Formalizing Embeddedness Failures in Universal Artificial Intelligence. CoRR Cole Wyeth, Marcus Hutter
2025	J	`jnl`	Imitation learning is probably existentially safe. AI Mag. Michael K. Cohen, Marcus Hutter
2025	J	`jnl`	Limit-Computable Grains of Truth for Arbitrary Computable Extensive-Form (Un)Known Games. CoRR Cole Wyeth, Marcus Hutter, Jan Leike, Jessica Taylor
2025	J	`jnl`	Partition Tree Weighting for Non-Stationary Stochastic Bandits. CoRR Joel Veness, Marcus Hutter, András György, Jordi Grau-Moya
2025	J	`jnl`	Properties of Algorithmic Information Distance. CoRR Marcus Hutter
2025	J	`jnl`	Properties of Algorithmic Information Distance. IEEE Trans. Inf. Theory Marcus Hutter
2025	A	`conf`	RL, but don't do anything I wouldn't do. UAI Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell
2025	J	`jnl`	Understanding Prompt Tuning and In-Context Learning via Meta-Learning. CoRR Tim Genewein, Li Kevin Wenliang, Jordi Grau-Moya, Anian Ruoss, Laurent Orseau, Marcus Hutter
2025	—	`conf`	Value Under Ignorance in Universal Artificial Intelligence. AGI (2) Cole Wyeth, Marcus Hutter
2025	J	`jnl`	Value Under Ignorance in Universal Artificial Intelligence. CoRR Cole Wyeth, Marcus Hutter
2025	J	`jnl`	Why is prompting hard? Understanding prompts on binary sequence predictors. CoRR Li Kevin Wenliang, Anian Ruoss, Jordi Grau-Moya, Marcus Hutter, Tim Genewein
2024	A*	`conf`	Distributional Bellman Operators over Mean Embeddings. ICML Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland
2024	A*	`conf`	Dynamic Knowledge Injection for AIXI Agents. AAAI Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
2024	J	`jnl`	Evaluating Frontier Models for Dangerous Capabilities. CoRR 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
2024	J	`jnl`	Exponential Speedups by Rerooting Levin Tree Search. CoRR Laurent Orseau, Marcus Hutter, Levi H. S. Lelis
2024	A*	`conf`	Language Modeling Is Compression. ICLR 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
2024	A*	`conf`	Learning Universal Predictors. ICML Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
2024	J	`jnl`	Learning Universal Predictors. CoRR Jordi Grau-Moya, Tim Genewein, Marcus Hutter, Laurent Orseau, Grégoire Delétang, Elliot Catt, Anian Ruoss, Li Kevin Wenliang, Christopher Mattern, Matthew Aitchison, Joel Veness
2024	J	`jnl`	Modeling the Arrows of Time with Causal Multibaker Maps. Entropy Aram Ebtekar, Marcus Hutter
2024	J	`jnl`	RL, but don't do anything I wouldn't do. CoRR Michael K. Cohen, Marcus Hutter, Yoshua Bengio, Stuart Russell
2024	J	`jnl`	Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models. CoRR Amal Rannen-Triki, Jörg Bornschein, Razvan Pascanu, Marcus Hutter, András György, Alexandre Galashov, Yee Whye Teh, Michalis K. Titsias
2023	A*	`conf`	Atari-5: Distilling the Arcade Learning Environment down to Five Games. ICML Matthew Aitchison, Penny Sweetser, Marcus Hutter
2023	J	`jnl`	Bridging Algorithmic Information Theory and Machine Learning: A New Approach to Kernel Learning. CoRR Boumediene Hamzi, Marcus Hutter, Houman Owhadi
2023	J	`jnl`	Combining a Meta-Policy and Monte-Carlo Planning for Scalable Type-Based Reasoning in Partially Observable Environments. CoRR Jonathon Schwartz, Hanna Kurniawati, Marcus Hutter
2023	J	`jnl`	Distributional Bellman Operators over Mean Embeddings. CoRR Li Kevin Wenliang, Grégoire Delétang, Matthew Aitchison, Marcus Hutter, Anian Ruoss, Arthur Gretton, Mark Rowland
2023	J	`jnl`	Dynamic Knowledge Injection for AIXI Agents. CoRR Samuel Yang-Zhao, Kee Siong Ng, Marcus Hutter
2023	A*	`conf`	Evaluating Representations with Readout Model Switching. ICLR Yazhe Li, Jörg Bornschein, Marcus Hutter
2023	J	`jnl`	Evaluating Representations with Readout Model Switching. CoRR Yazhe Li, Jörg Bornschein, Marcus Hutter
2023	J	`jnl`	Language Modeling Is Compression. CoRR 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
2023	A*	`conf`	Levin Tree Search with Context Models. IJCAI Laurent Orseau, Marcus Hutter, Levi H. S. Lelis
2023	J	`jnl`	Levin Tree Search with Context Models. CoRR Laurent Orseau, Marcus Hutter, Levi H. S. Lelis
2023	J	`jnl`	Line Search for Convex Minimization. CoRR Laurent Orseau, Marcus Hutter
2023	A*	`conf`	Memory-Based Meta-Learning on Non-Stationary Distributions. ICML Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
2023	J	`jnl`	Memory-Based Meta-Learning on Non-Stationary Distributions. CoRR Tim Genewein, Grégoire Delétang, Anian Ruoss, Li Kevin Wenliang, Elliot Catt, Vincent Dutordoir, Jordi Grau-Moya, Laurent Orseau, Marcus Hutter, Joel Veness
2023	A*	`conf`	Neural Networks and the Chomsky Hierarchy. ICLR 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
2023	A*	`conf`	Self-Predictive Universal AI. NeurIPS Elliot Catt, Jordi Grau-Moya, Marcus Hutter, Matthew Aitchison, Tim Genewein, Grégoire Delétang, Kevin Li, Joel Veness
2023	A*	`conf`	Sequential Learning of Neural Networks for Prequential MDL. ICLR Jörg Bornschein, Yazhe Li, Marcus Hutter
2023	J	`jnl`	U-Clip: On-Average Unbiased Stochastic Gradient Clipping. CoRR Bryn Elesedy, Marcus Hutter
2023	A	`conf`	Universal Agent Mixtures and the Geometry of Intelligence. AISTATS Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter
2023	J	`jnl`	Universal Agent Mixtures and the Geometry of Intelligence. CoRR Samuel Allen Alexander, David Quarel, Len Du, Marcus Hutter
2022	J	`jnl`	Advanced Artificial Agents Intervene in the Provision of Reward. AI Mag. Michael K. Cohen, Marcus Hutter, Michael A. Osborne
2022	J	`jnl`	Atari-5: Distilling the Arcade Learning Environment down to Five Games. CoRR Matthew Aitchison, Penny Sweetser, Marcus Hutter
2022	J	`jnl`	Beyond Bayes-optimality: meta-learning what you know you don't know. CoRR 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
2022	J	`jnl`	Formal Algorithms for Transformers. CoRR Mary Phuong, Marcus Hutter
2022	J	`jnl`	Fully General Online Imitation Learning. J. Mach. Learn. Res. Michael K. Cohen, Marcus Hutter, Neel Nanda
2022	J	`jnl`	Generalization Bounds for Transfer Learning with Pretrained Classifiers. CoRR Tomer Galanti, András György, Marcus Hutter
2022	J	`jnl`	Neural Networks and the Chomsky Hierarchy. CoRR Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, Tim Genewein, Li Kevin Wenliang, Elliot Catt, Marcus Hutter, Shane Legg, Pedro A. Ortega
2022	A*	`conf`	On the Role of Neural Collapse in Transfer Learning. ICLR Tomer Galanti, András György, Marcus Hutter
2022	—	`conf`	Reinforcement Learning with Information-Theoretic Actuation. AGI Elliot Catt, Marcus Hutter, Joel Veness
2022	J	`jnl`	Sequential Learning Of Neural Networks for Prequential MDL. CoRR Jörg Bornschein, Yazhe Li, Marcus Hutter
2022	J	`jnl`	Testing Independence of Exchangeable Random Variables. CoRR Marcus Hutter
2022	J	`jnl`	Uniqueness and Complexity of Inverse MDP Models. CoRR Marcus Hutter, Steven Hansen
2021	A*	`conf`	Counterfactual Credit Assignment in Model-Free Reinforcement Learning. ICML 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
2021	J	`jnl`	Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal Agent. IEEE J. Sel. Areas Inf. Theory Michael K. Cohen, Elliot Catt, Marcus Hutter
2021	A*	`conf`	Exact Reduction of Huge Action Spaces in General Reinforcement Learning. AAAI Sultan Javed Majeed, Marcus Hutter
2021	J	`jnl`	Feature Reinforcement Learning: Part II. Structured MDPs. J. Artif. Gen. Intell. Marcus Hutter
2021	J	`jnl`	Fully General Online Imitation Learning. CoRR Michael K. Cohen, Marcus Hutter, Neel Nanda
2021	A*	`conf`	Gated Linear Networks. AAAI Joel Veness, Tor Lattimore, David Budden, Avishkar Bhoopchand, Christopher Mattern, Agnieszka Grabska-Barwinska, Eren Sezener, Jianan Wang, Peter Toth, Simon Schmitt, Marcus Hutter
2021	—	`conf`	How Useful are Hand-crafted Data? Making Cases for Anomaly Detection Methods. HICSS Len Du, Marcus Hutter
2021	J	`jnl`	Intelligence and Unambitiousness Using Algorithmic Information Theory. CoRR Michael K. Cohen, Badri N. Vellambi, Marcus Hutter
2021	J	`jnl`	Intelligence and Unambitiousness Using Algorithmic Information Theory. IEEE J. Sel. Areas Inf. Theory Michael K. Cohen, Badri N. Vellambi, Marcus Hutter
2021	J	`jnl`	Isotuning With Applications To Scale-Free Online Learning. CoRR Laurent Orseau, Marcus Hutter
2021	J	`jnl`	Learning Curve Theory. CoRR Marcus Hutter
2021	J	`jnl`	On the Role of Neural Collapse in Transfer Learning. CoRR Tomer Galanti, András György, Marcus Hutter
2021	J	`jnl`	Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions. CoRR Sultan Javed Majeed, Marcus Hutter
2021	J	`jnl`	Reinforcement Learning with Information-Theoretic Actuation. CoRR Elliot Catt, Marcus Hutter, Joel Veness
2021	J	`jnl`	Reward tampering problems and solutions in reinforcement learning: a causal influence diagram perspective. Synth. Tom Everitt, Marcus Hutter, Ramana Kumar, Victoria Krakovna
2021	—	`conf`	Reward-Punishment Symmetric Universal Intelligence. AGI Samuel Allen Alexander, Marcus Hutter
2021	J	`jnl`	Reward-Punishment Symmetric Universal Intelligence. CoRR Samuel Allen Alexander, Marcus Hutter
2021	J	`jnl`	Shaking the foundations: delusions in sequence models for interaction and control. CoRR 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
2020	A*	`conf`	A Combinatorial Perspective on Transfer Learning. NeurIPS Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
2020	J	`jnl`	A Combinatorial Perspective on Transfer Learning. CoRR Jianan Wang, Eren Sezener, David Budden, Marcus Hutter, Joel Veness
2020	J	`jnl`	A Gentle Introduction to Quantum Computing Algorithms with Applications to Universal Prediction. CoRR Elliot Catt, Marcus Hutter
2020	A*	`conf`	Asymptotically Unambitious Artificial General Intelligence. AAAI Michael K. Cohen, Badri N. Vellambi, Marcus Hutter
2020	J	`jnl`	Counterfactual Credit Assignment in Model-Free Reinforcement Learning. CoRR 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
2020	J	`jnl`	Curiosity Killed the Cat and the Asymptotically Optimal Agent. CoRR Michael K. Cohen, Marcus Hutter
2020	J	`jnl`	Exact Reduction of Huge Action Spaces in General Reinforcement Learning. CoRR Sultan Javed Majeed, Marcus Hutter
2020	A*	`conf`	Logarithmic Pruning is All You Need. NeurIPS Laurent Orseau, Marcus Hutter, Omar Rivasplata
2020	J	`jnl`	Logarithmic Pruning is All You Need. CoRR Laurent Orseau, Marcus Hutter, Omar Rivasplata
2020	J	`jnl`	On Representing (Anti)Symmetric Functions. CoRR Marcus Hutter
2020	A*	`conf`	Online Learning in Contextual Bandits using Gated Linear Networks. NeurIPS Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness
2020	J	`jnl`	Online Learning in Contextual Bandits using Gated Linear Networks. CoRR Eren Sezener, Marcus Hutter, David Budden, Jianan Wang, Joel Veness
2020	A*	`conf`	Pessimism About Unknown Unknowns Inspires Conservatism. COLT Michael K. Cohen, Marcus Hutter
2020	J	`jnl`	Pessimism About Unknown Unknowns Inspires Conservatism. CoRR Michael K. Cohen, Marcus Hutter
2019	A*	`conf`	A Strongly Asymptotically Optimal Agent in General Environments. IJCAI Michael K. Cohen, Elliot Catt, Marcus Hutter
2019	J	`jnl`	Asymptotically Unambitious Artificial General Intelligence. CoRR Michael K. Cohen, Badri N. Vellambi, Marcus Hutter
2019	A*	`conf`	Conditions on Features for Temporal Difference-Like Methods to Converge. IJCAI Marcus Hutter, Samuel Yang-Zhao, Sultan Javed Majeed
2019	J	`jnl`	Conditions on Features for Temporal Difference-Like Methods to Converge. CoRR Marcus Hutter, Samuel Yang-Zhao, Sultan Javed Majeed
2019	J	`jnl`	Fairness without Regret. CoRR Marcus Hutter
2019	J	`jnl`	Gated Linear Networks. CoRR Joel Veness, Tor Lattimore, Avishkar Bhoopchand, David Budden, Christopher Mattern, Agnieszka Grabska-Barwinska, Peter Toth, Simon Schmitt, Marcus Hutter
2019	A*	`conf`	Performance Guarantees for Homomorphisms beyond Markov Decision Processes. AAAI Sultan Javed Majeed, Marcus Hutter
2019	J	`jnl`	Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective. CoRR Tom Everitt, Marcus Hutter
2019	J	`jnl`	Strong Asymptotic Optimality in General Environments. CoRR Michael K. Cohen, Elliot Catt, Marcus Hutter
2018	A*	`conf`	AGI Safety Literature Review. IJCAI Tom Everitt, Gary Lea, Marcus Hutter
2018	J	`jnl`	AGI Safety Literature Review. CoRR Tom Everitt, Gary Lea, Marcus Hutter
2018	B	`conf`	Convergence of Binarized Context-tree Weighting for Estimating Distributions of Stationary Sources. ISIT Badri N. Vellambi, Marcus Hutter
2018	A*	`conf`	On Q-learning Convergence for Non-Markov Decision Processes. IJCAI Sultan Javed Majeed, Marcus Hutter
2018	J	`jnl`	On the computability of Solomonoff induction and AIXI. Theor. Comput. Sci. Jan Leike, Marcus Hutter
2018	J	`jnl`	Performance Guarantees for Homomorphisms Beyond Markov Decision Processes. CoRR Sultan Javed Majeed, Marcus Hutter
2018	J	`jnl`	Tractability of batch to sequential conversion. Theor. Comput. Sci. Marcus Hutter
2018	B	`conf`	Universal Compression of Piecewise i.i.d. Sources. DCC Badri N. Vellambi, Cameron Owen, Marcus Hutter
2017	—	`conf`	A Game-Theoretic Analysis of the Off-Switch Game. AGI Tobias Wängberg, Mikael Böörs, Elliot Catt, Tom Everitt, Marcus Hutter
2017	J	`jnl`	A Game-Theoretic Analysis of the Off-Switch Game. CoRR Tobias Wängberg, Mikael Böörs, Elliot Catt, Tom Everitt, Marcus Hutter
2017	A*	`conf`	Count-Based Exploration in Feature Space for Reinforcement Learning. IJCAI Jarryd Martin, Suraj Narayanan Sasikumar, Tom Everitt, Marcus Hutter
2017	J	`jnl`	Count-Based Exploration in Feature Space for Reinforcement Learning. CoRR Jarryd Martin, Suraj Narayanan Sasikumar, Tom Everitt, Marcus Hutter
2017	A	`conf`	Generalised Discount Functions applied to a Monte-Carlo AI u Implementation. AAMAS Sean Lamont, John Aslanides, Jan Leike, Marcus Hutter
2017	J	`jnl`	Generalised Discount Functions applied to a Monte-Carlo AImu Implementation. CoRR Sean Lamont, John Aslanides, Jan Leike, Marcus Hutter
2017	A*	`conf`	On Thompson Sampling and Asymptotic Optimality. IJCAI Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
2017	J	`jnl`	Reinforcement Learning with a Corrupted Reward Channel. CoRR Tom Everitt, Victoria Krakovna, Laurent Orseau, Marcus Hutter, Shane Legg
2017	—	`ch.`	Universal Learning Theory. Encyclopedia of Machine Learning and Data Mining Marcus Hutter
2017	A*	`conf`	Universal Reinforcement Learning Algorithms: Survey and Experiments. IJCAI John Aslanides, Jan Leike, Marcus Hutter
2017	J	`jnl`	Universal Reinforcement Learning Algorithms: Survey and Experiments. CoRR John Aslanides, Jan Leike, Marcus Hutter
2016	—	`conf`	Avoiding Wireheading with Value Reinforcement Learning. AGI Tom Everitt, Marcus Hutter
2016	J	`jnl`	Avoiding Wireheading with Value Reinforcement Learning. CoRR Tom Everitt, Marcus Hutter
2016	—	`conf`	Death and Suicide in Universal Artificial Intelligence. AGI Jarryd Martin, Tom Everitt, Marcus Hutter
2016	J	`jnl`	Death and Suicide in Universal Artificial Intelligence. CoRR Jarryd Martin, Tom Everitt, Marcus Hutter
2016	A*	`conf`	Discriminative Hierarchical Rank Pooling for Activity Recognition. CVPR Basura Fernando, Peter Anderson, Marcus Hutter, Stephen Gould
2016	J	`jnl`	Extreme state aggregation beyond Markov decision processes. Theor. Comput. Sci. Marcus Hutter
2016	J	`jnl`	Free Lunch for Optimisation under the Universal Distribution. CoRR Tom Everitt, Tor Lattimore, Marcus Hutter
2016	A	`conf`	Loss Bounds and Time Complexity for Speed Priors. AISTATS Daniel Filan, Jan Leike, Marcus Hutter
2016	J	`jnl`	Loss Bounds and Time Complexity for Speed Priors. CoRR Daniel Filan, Marcus Hutter, Jan Leike
2016	—	`conf`	Self-Modification of Policy and Utility Function in Rational Agents. AGI Tom Everitt, Daniel Filan, Mayank Daswani, Marcus Hutter
2016	J	`jnl`	Self-Modification of Policy and Utility Function in Rational Agents. CoRR Tom Everitt, Daniel Filan, Mayank Daswani, Marcus Hutter
2016	A	`conf`	Thompson Sampling is Asymptotically Optimal in General Environments. UAI Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
2016	J	`jnl`	Thompson Sampling is Asymptotically Optimal in General Environments. CoRR Jan Leike, Tor Lattimore, Laurent Orseau, Marcus Hutter
2015	J	`jnl`	A Topological Approach to Meta-heuristics: Analytical Results on the BFS vs. DFS Algorithm Selection Problem. CoRR Tom Everitt, Marcus Hutter
2015	—	`conf`	Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search. Australasian Conference on Artificial Intelligence Tom Everitt, Marcus Hutter
2015	—	`conf`	Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search. Australasian Conference on Artificial Intelligence Tom Everitt, Marcus Hutter
2015	A*	`conf`	Bad Universal Priors and Notions of Optimality. COLT Jan Leike, Marcus Hutter
2015	J	`jnl`	Bad Universal Priors and Notions of Optimality. CoRR Jan Leike, Marcus Hutter
2015	A*	`conf`	Compress and Control. AAAI Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
2015	J	`jnl`	On Martin-Löf (non-)convergence of Solomonoff's universal mixture. Theor. Comput. Sci. Tor Lattimore, Marcus Hutter
2015	A	`conf`	On the Computability of AIXI. UAI Jan Leike, Marcus Hutter
2015	J	`jnl`	On the Computability of AIXI. CoRR Jan Leike, Marcus Hutter
2015	B	`conf`	On the Computability of Solomonoff Induction and Knowledge-Seeking. ALT Jan Leike, Marcus Hutter
2015	J	`jnl`	On the Computability of Solomonoff Induction and Knowledge-Seeking. CoRR Jan Leike, Marcus Hutter
2015	A*	`conf`	Online Learning of k-CNF Boolean Functions. IJCAI Joel Veness, Marcus Hutter, Laurent Orseau, Marc G. Bellemare
2015	J	`jnl`	Rationality, optimism and guarantees in general reinforcement learning. J. Mach. Learn. Res. Peter Sunehag, Marcus Hutter
2015	—	`conf`	Sequential Extensions of Causal and Evidential Decision Theory. ADT Tom Everitt, Jan Leike, Marcus Hutter
2015	J	`jnl`	Sequential Extensions of Causal and Evidential Decision Theory. CoRR Tom Everitt, Jan Leike, Marcus Hutter
2015	B	`conf`	Solomonoff Induction Violates Nicod's Criterion. ALT Jan Leike, Marcus Hutter
2015	J	`jnl`	Solomonoff Induction Violates Nicod's Criterion. CoRR Jan Leike, Marcus Hutter
2015	—	`conf`	Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning. AGI Peter Sunehag, Marcus Hutter
2014	B	`conf`	A Dual Process Theory of Optimistic Cognition. CogSci Peter Sunehag, Marcus Hutter
2014	J	`jnl`	Asymptotics of Continuous Bayes for Non-i.i.d. Sources. CoRR Tor Lattimore, Marcus Hutter
2014	B	`conf`	Bayesian Reinforcement Learning with Exploration. ALT Tor Lattimore, Marcus Hutter
2014	B	`conf`	Can we measure the difficulty of an optimization problem? ITW Tansu Alpcan, Tom Everitt, Marcus Hutter
2014	J	`jnl`	Compress and Control. CoRR Joel Veness, Marc G. Bellemare, Marcus Hutter, Alvin Chua, Guillaume Desjardins
2014	J	`jnl`	Extreme State Aggregation Beyond MDPs. CoRR Marcus Hutter
2014	B	`conf`	Extreme State Aggregation beyond MDPs. ALT Marcus Hutter
2014	B	`conf`	Free Lunch for optimisation under the universal distribution. IEEE Congress on Evolutionary Computation Tom Everitt, Tor Lattimore, Marcus Hutter
2014	J	`jnl`	General time consistent discounting. Theor. Comput. Sci. Tor Lattimore, Marcus Hutter
2014	B	`conf`	Indefinitely Oscillating Martingales. ALT Jan Leike, Marcus Hutter
2014	J	`jnl`	Indefinitely Oscillating Martingales. CoRR Jan Leike, Marcus Hutter
2014	—	`conf`	Intelligence as Inference or Forcing Occam on the World. AGI Peter Sunehag, Marcus Hutter
2014	J	`jnl`	Near-optimal PAC bounds for discounted MDPs. Theor. Comput. Sci. Tor Lattimore, Marcus Hutter
2014	B	`conf`	Offline to Online Conversion. ALT Marcus Hutter
2014	J	`jnl`	Offline to Online Conversion. CoRR Marcus Hutter
2014	J	`jnl`	Online Learning of k-CNF Boolean Functions. CoRR Joel Veness, Marcus Hutter
2014	Misc	`conf`	Reflective Features Detection and Hierarchical Reflections Separation in Image Sequences. DICTA Di Yang, Srimal Jayawardena, Stephen Gould, Marcus Hutter
2014	C	`conf`	Reinforcement learning with value advice. ACML Mayank Daswani, Peter Sunehag, Marcus Hutter
2014	—	`conf`	Reliable Point Correspondences in Scenes Dominated by Highly Reflective and Largely Homogeneous Surfaces. ACCV Workshops (1) Srimal Jayawardena, Stephen Gould, Hongdong Li, Marcus Hutter, Richard I. Hartley
2014	J	`jnl`	Robust Feature Selection by Mutual Information Distributions. CoRR Marco Zaffalon, Marcus Hutter
2013	J	`jnl`	A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation. CoRR Srimal Jayawardena, Marcus Hutter, Nathan Brewer
2013	B	`conf`	Concentration and Confidence for Discrete Bayesian Sequence Predictors. ALT Tor Lattimore, Marcus Hutter, Peter Sunehag
2013	J	`jnl`	Concentration and Confidence for Discrete Bayesian Sequence Predictors. CoRR Tor Lattimore, Marcus Hutter, Peter Sunehag
2013	J	`jnl`	Guest Editors' foreword. Theor. Comput. Sci. Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann
2013	—	`conf`	Learning Agents with Evolving Hypothesis Classes. AGI Peter Sunehag, Marcus Hutter
2013	C	`conf`	On Martin-Löf Convergence of Solomonoff's Mixture. TAMC Tor Lattimore, Marcus Hutter
2013	J	`jnl`	Probabilities on Sentences in an Expressive Logic. J. Appl. Log. Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther
2013	C	`conf`	Q-learning for history-based reinforcement learning. ACML Mayank Daswani, Peter Sunehag, Marcus Hutter
2013	J	`jnl`	Reinforcement Learning (Dagstuhl Seminar 13321). Dagstuhl Reports Peter Auer, Marcus Hutter, Laurent Orseau
2013	J	`jnl`	Sparse Adaptive Dirichlet-Multinomial-like Processes CoRR Marcus Hutter
2013	A*	`conf`	Sparse Adaptive Dirichlet-Multinomial-like Processes. COLT Marcus Hutter
2013	—	`conf`	The Sample-Complexity of General Reinforcement Learning. ICML (3) Tor Lattimore, Marcus Hutter, Peter Sunehag
2013	J	`jnl`	The Sample-Complexity of General Reinforcement Learning. CoRR Tor Lattimore, Marcus Hutter, Peter Sunehag
2013	B	`conf`	Universal Knowledge-Seeking Agents for Stochastic Environments. ALT Laurent Orseau, Tor Lattimore, Marcus Hutter
2012	J	`jnl`	3D Model Assisted Image Segmentation CoRR Srimal Jayawardena, Di Yang, Marcus Hutter
2012	—	`conf`	A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation. ACCV (1) Di Yang, Stephen Gould, Marcus Hutter
2012	J	`jnl`	Adaptive Context Tree Weighting CoRR Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag
2012	B	`conf`	Adaptive Context Tree Weighting. DCC Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag
2012	J	`jnl`	Can Intelligence Explode? CoRR Marcus Hutter
2012	Misc	`conf`	Coding of Non-Stationary Sources as a Foundation for Detecting Change Points and Outliers in Binary Time-Series. AusDM Peter Sunehag, Wen Shao, Marcus Hutter
2012	A*	`conf`	Context Tree Maximizing. AAAI Phuong Nguyen, Peter Sunehag, Marcus Hutter
2012	B	`conf`	Context Tree Switching. DCC Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
2012	—	`conf`	Feature Reinforcement Learning using Looping Suffix Trees. EWRL Mayank Daswani, Peter Sunehag, Marcus Hutter
2012	—	`conf`	On Ensemble Techniques for AIXI Approximation. AGI Joel Veness, Peter Sunehag, Marcus Hutter
2012	J	`jnl`	One Decade of Universal Artificial Intelligence CoRR Marcus Hutter
2012	—	`conf`	Optimistic AIXI. AGI Peter Sunehag, Marcus Hutter
2012	—	`conf`	Optimistic Agents Are Asymptotically Optimal. Australasian Conference on Artificial Intelligence Peter Sunehag, Marcus Hutter
2012	J	`jnl`	Optimistic Agents are Asymptotically Optimal CoRR Peter Sunehag, Marcus Hutter
2012	J	`jnl`	PAC Bounds for Discounted MDPs CoRR Tor Lattimore, Marcus Hutter
2012	B	`conf`	PAC Bounds for Discounted MDPs. ALT Tor Lattimore, Marcus Hutter
2012	J	`jnl`	Probabilities on Sentences in an Expressive Logic CoRR Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther
2012	—	`ed.`	Recent Advances in Reinforcement Learning - 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised Selected Papers EWRL Scott Sanner, Marcus Hutter
2012	J	`jnl`	Sparse Sequential Dirichlet Coding CoRR Joel Veness, Marcus Hutter
2011	J	`jnl`	(Non-)Equivalence of Universal Priors CoRR Ian Wood, Peter Sunehag, Marcus Hutter
2011	—	`conf`	(Non-)Equivalence of Universal Priors. Algorithmic Probability and Friends Ian Wood, Peter Sunehag, Marcus Hutter
2011	Misc	`conf`	3D Model Assisted Image Segmentation. DICTA Srimal Jayawardena, Di Yang, Marcus Hutter
2011	J	`jnl`	A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver
2011	Misc	`conf`	A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation. DICTA Srimal Jayawardena, Marcus Hutter, Nathan Brewer
2011	J	`jnl`	A Philosophical Treatise of Universal Induction CoRR Samuel Rathmanner, Marcus Hutter
2011	J	`jnl`	A Philosophical Treatise of Universal Induction. Entropy Samuel Rathmanner, Marcus Hutter
2011	J	`jnl`	Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence CoRR Marcus Hutter
2011	J	`jnl`	Asymptotically Optimal Agents CoRR Tor Lattimore, Marcus Hutter
2011	B	`conf`	Asymptotically Optimal Agents. ALT Tor Lattimore, Marcus Hutter
2011	J	`jnl`	Axioms for Rational Reinforcement Learning CoRR Peter Sunehag, Marcus Hutter
2011	B	`conf`	Axioms for Rational Reinforcement Learning. ALT Peter Sunehag, Marcus Hutter
2011	J	`jnl`	Context Tree Switching CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling
2011	J	`jnl`	Feature Reinforcement Learning In Practice CoRR Phuong Nguyen, Peter Sunehag, Marcus Hutter
2011	—	`conf`	Feature Reinforcement Learning in Practice. EWRL Phuong Nguyen, Peter Sunehag, Marcus Hutter
2011	J	`jnl`	No Free Lunch versus Occam's Razor in Supervised Learning CoRR Tor Lattimore, Marcus Hutter
2011	—	`conf`	No Free Lunch versus Occam's Razor in Supervised Learning. Algorithmic Probability and Friends Tor Lattimore, Marcus Hutter
2011	J	`jnl`	Principles of Solomonoff Induction and AIXI CoRR Peter Sunehag, Marcus Hutter
2011	—	`conf`	Principles of Solomonoff Induction and AIXI. Algorithmic Probability and Friends Peter Sunehag, Marcus Hutter
2011	J	`jnl`	Time Consistent Discounting CoRR Tor Lattimore, Marcus Hutter
2011	B	`conf`	Time Consistent Discounting. ALT Tor Lattimore, Marcus Hutter
2011	J	`jnl`	Universal Learning Theory CoRR Marcus Hutter
2011	J	`jnl`	Universal Prediction of Selected Bits CoRR Tor Lattimore, Marcus Hutter, Vaibhav Gavane
2011	B	`conf`	Universal Prediction of Selected Bits. ALT Tor Lattimore, Marcus Hutter, Vaibhav Gavane
2010	J	`jnl`	A Bayesian Review of the Poisson-Dirichlet Process CoRR Wray L. Buntine, Marcus Hutter
2010	J	`jnl`	A Complete Theory of Everything (Will Be Subjective). Algorithms Marcus Hutter
2010	B	`ed.`	Algorithmic Learning Theory, 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings ALT Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann
2010	J	`jnl`	An integrated Bayesian analysis of LOH and copy number data. BMC Bioinform. Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee
2010	J	`jnl`	Consistency of Feature Markov Processes CoRR Peter Sunehag, Marcus Hutter
2010	B	`conf`	Consistency of Feature Markov Processes. ALT Peter Sunehag, Marcus Hutter
2010	B	`conf`	Editors' Introduction. ALT Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann
2010	J	`jnl`	Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss CoRR Srimal Jayawardena, Marcus Hutter, Nathan Brewer
2010	J	`jnl`	Model Selection with the Loss Rank Principle CoRR Marcus Hutter, Minh-Ngoc Tran
2010	J	`jnl`	Model selection with the Loss Rank Principle. Comput. Stat. Data Anal. Marcus Hutter, Minh-Ngoc Tran
2010	J	`jnl`	Reinforcement Learning via AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2010	A*	`conf`	Reinforcement Learning via AIXI Approximation. AAAI Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2010	J	`jnl`	Report on the Third Conference on Artificial General Intelligence. AI Mag. Ben Goertzel, Marcus Hutter
2010	—	`ch.`	Universal Learning Theory. Encyclopedia of Machine Learning Marcus Hutter
2009	J	`jnl`	A Complete Theory of Everything (will be subjective) CoRR Marcus Hutter
2009	J	`jnl`	A Monte Carlo AIXI Approximation CoRR Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver
2009	J	`jnl`	A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data CoRR Ke Zhang, Marcus Hutter, Huidong Jin
2009	B	`conf`	A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data. PAKDD Ke Zhang, Marcus Hutter, Huidong Jin
2009	J	`jnl`	Bayesian DNA copy number analysis. BMC Bioinform. Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee
2009	—	`conf`	Bayesian Joint Estimation of CN and LOH Aberrations. IWANN (2) Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee
2009	—	`conf`	Discrete MDL Predicts in Total Variation. NIPS Marcus Hutter
2009	J	`jnl`	Discrete MDL Predicts in Total Variation. CoRR Marcus Hutter
2009	J	`jnl`	Exact Non-Parametric Bayesian Inference on Infinite Trees. CoRR Marcus Hutter
2009	J	`jnl`	Feature Reinforcement Learning: Part I. Unstructured MDPs. J. Artif. Gen. Intell. Marcus Hutter
2009	J	`jnl`	Feature Reinforcement Learning: Part I: Unstructured MDPs CoRR Marcus Hutter
2009	J	`jnl`	Limits of Learning about a Categorical Latent Variable under Prior Near-Ignorance CoRR Alberto Piatti, Marco Zaffalon, Fabio Trojani, Marcus Hutter
2009	J	`jnl`	Limits of learning about a categorical latent variable under prior near-ignorance. Int. J. Approx. Reason. Alberto Piatti, Marco Zaffalon, Fabio Trojani, Marcus Hutter
2009	J	`jnl`	Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation CoRR Marcus Hutter, Nathan Brewer
2009	J	`jnl`	Open Problems in Universal Induction & Intelligence CoRR Marcus Hutter
2009	J	`jnl`	Open Problems in Universal Induction & Intelligence. Algorithms Marcus Hutter
2009	J	`jnl`	Practical Robust Estimators for the Imprecise Dirichlet Model. CoRR Marcus Hutter
2009	J	`jnl`	Practical robust estimators for the imprecise Dirichlet model. Int. J. Approx. Reason. Marcus Hutter
2009	J	`jnl`	Preface. Theor. Comput. Sci. Marcus Hutter, Rocco A. Servedio
2008	J	`jnl`	Algorithmic complexity. Scholarpedia Marcus Hutter
2008	J	`jnl`	Equivalence of Probabilistic Tournament and Polynomial Ranking Selection CoRR Kassel Hingee, Marcus Hutter
2008	B	`conf`	Equivalence of probabilistic tournament and polynomial ranking selection. IEEE Congress on Evolutionary Computation Kassel Hingee, Marcus Hutter
2008	J	`jnl`	Feature Dynamic Bayesian Networks CoRR Marcus Hutter
2008	J	`jnl`	Feature Markov Decision Processes CoRR Marcus Hutter
2008	J	`jnl`	On the Possibility of Learning in Reactive Environments with Arbitrary Dependence CoRR Daniil Ryabko, Marcus Hutter
2008	J	`jnl`	On the possibility of learning in reactive environments with arbitrary dependence. Theor. Comput. Sci. Daniil Ryabko, Marcus Hutter
2008	J	`jnl`	Predicting non-stationary processes. Appl. Math. Lett. Daniil Ryabko, Marcus Hutter
2008	J	`jnl`	Predictive Hypothesis Identification CoRR Marcus Hutter
2008	J	`jnl`	Temporal Difference Updating without a Learning Rate CoRR Marcus Hutter, Shane Legg
2007	J	`jnl`	A Collection of Definitions of Intelligence CoRR Shane Legg, Marcus Hutter
2007	J	`jnl`	Algorithmic Complexity Bounds on Future Prediction Errors CoRR Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber
2007	J	`jnl`	Algorithmic Information Theory: a brief non-technical guide to the field CoRR Marcus Hutter
2007	B	`ed.`	Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings ALT Marcus Hutter, Rocco A. Servedio, Eiji Takimoto
2007	J	`jnl`	Algorithmic complexity bounds on future prediction errors. Inf. Comput. Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber
2007	J	`jnl`	Algorithmic information theory. Scholarpedia Marcus Hutter
2007	J	`jnl`	Algorithmic probability. Scholarpedia Marcus Hutter, Shane Legg, Paul M. B. Vitányi
2007	B	`conf`	Editors' Introduction. ALT Marcus Hutter, Rocco A. Servedio, Eiji Takimoto
2007	J	`jnl`	On Semimeasures Predicting Martin-Loef Random Sequences CoRR Marcus Hutter, Andrej Muchnik
2007	B	`conf`	On Sequence Prediction for Arbitrary Measures. ISIT Daniil Ryabko, Marcus Hutter
2007	J	`jnl`	On Universal Prediction and Bayesian Confirmation CoRR Marcus Hutter
2007	J	`jnl`	On semimeasures predicting Martin-Löf random sequences. Theor. Comput. Sci. Marcus Hutter, Andrej Muchnik
2007	J	`jnl`	On universal prediction and Bayesian confirmation. Theor. Comput. Sci. Marcus Hutter
2007	—	`conf`	Temporal Difference Updating without a Learning Rate. NIPS Marcus Hutter, Shane Legg
2007	J	`jnl`	Tests of Machine Intelligence CoRR Shane Legg, Marcus Hutter
2007	J	`jnl`	The Loss Rank Principle for Model Selection CoRR Marcus Hutter
2007	A*	`conf`	The Loss Rank Principle for Model Selection. COLT Marcus Hutter
2007	—	`ch.`	Universal Algorithmic Intelligence: A Mathematical Top→Down Approach. Artificial General Intelligence Marcus Hutter
2007	J	`jnl`	Universal Algorithmic Intelligence: A mathematical top->down approach CoRR Marcus Hutter
2007	J	`jnl`	Universal Intelligence: A Definition of Machine Intelligence CoRR Shane Legg, Marcus Hutter
2007	J	`jnl`	Universal Intelligence: A Definition of Machine Intelligence. Minds Mach. Shane Legg, Marcus Hutter
2006	—	`conf`	06051 Abstracts Collection -- Kolmogorov Complexity and Applications. Kolmogorov Complexity and Applications Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi
2006	—	`conf`	A Collection of Definitions of Intelligence. AGI Shane Legg, Marcus Hutter
2006	J	`jnl`	A Formal Measure of Machine Intelligence CoRR Shane Legg, Marcus Hutter
2006	J	`jnl`	Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence CoRR Daniil Ryabko, Marcus Hutter
2006	B	`conf`	Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence. ALT Daniil Ryabko, Marcus Hutter
2006	J	`jnl`	Bayesian Regression of Piecewise Constant Functions CoRR Marcus Hutter
2006	—	`conf`	Complexity Monotone in Conditions and Future Prediction Errors. Kolmogorov Complexity and Applications Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber
2006	J	`jnl`	Fitness Uniform Optimization CoRR Marcus Hutter, Shane Legg
2006	J	`jnl`	Fitness uniform optimization. IEEE Trans. Evol. Comput. Marcus Hutter, Shane Legg
2006	B	`conf`	General Discounting Versus Average Reward. ALT Marcus Hutter
2006	J	`jnl`	General Discounting versus Average Reward CoRR Marcus Hutter
2006	J	`jnl`	Hybrid rounding techniques for knapsack problems. Discret. Appl. Math. Monaldo Mastrolilli, Marcus Hutter
2006	—	`ed.`	Kolmogorov Complexity and Applications, 29.01. - 03.02.2006 Kolmogorov Complexity and Applications Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi
2006	—	`conf`	Learning in Reactive Environments with Arbitrary Dependence. Kolmogorov Complexity and Applications Daniil Ryabko, Marcus Hutter
2006	J	`jnl`	MDL Convergence Speed for Bernoulli Sequences CoRR Jan Poland, Marcus Hutter
2006	J	`jnl`	MDL convergence speed for Bernoulli sequences. Stat. Comput. Jan Poland, Marcus Hutter
2006	J	`jnl`	Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot CoRR Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber
2006	C	`conf`	Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot. IAS Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber
2006	J	`jnl`	On Sequence Prediction for Arbitrary Measures CoRR Daniil Ryabko, Marcus Hutter
2006	J	`jnl`	On generalized computable universal priors and their convergence. Theor. Comput. Sci. Marcus Hutter
2006	J	`jnl`	On the Foundations of Universal Sequence Prediction CoRR Marcus Hutter
2006	C	`conf`	On the Foundations of Universal Sequence Prediction. TAMC Marcus Hutter
2006	—	`conf`	Sequence prediction for non-stationary processes. Combinatorial and Algorithmic Foundations of Pattern and Association Discovery Daniil Ryabko, Marcus Hutter
2006	J	`jnl`	Sequential predictions based on algorithmic complexity. J. Comput. Syst. Sci. Marcus Hutter
2006	—	`conf`	Tests of Machine Intelligence. 50 Years of Artificial Intelligence Shane Legg, Marcus Hutter
2005	A*	`conf`	A Universal Measure of Intelligence for Artificial Agents. IJCAI Shane Legg, Marcus Hutter
2005	J	`jnl`	Adaptive Online Prediction by Following the Perturbed Leader CoRR Marcus Hutter, Jan Poland
2005	J	`jnl`	Adaptive Online Prediction by Following the Perturbed Leader. J. Mach. Learn. Res. Marcus Hutter, Jan Poland
2005	J	`jnl`	Asymptotics of Discrete MDL for Online Prediction CoRR Jan Poland, Marcus Hutter
2005	J	`jnl`	Asymptotics of discrete MDL for online prediction. IEEE Trans. Inf. Theory Jan Poland, Marcus Hutter
2005	J	`jnl`	Defensive Universal Learning with Experts CoRR Jan Poland, Marcus Hutter
2005	B	`conf`	Defensive Universal Learning with Experts. ALT Jan Poland, Marcus Hutter
2005	J	`jnl`	Distribution of mutual information from complete and incomplete data. Comput. Stat. Data Anal. Marcus Hutter, Marco Zaffalon
2005	A	`conf`	Fast Non-Parametric Bayesian Inference on Infinite Trees. AISTATS Marcus Hutter
2005	J	`jnl`	Fitness Uniform Deletion: A Simple Way to Preserve Diversity CoRR Shane Legg, Marcus Hutter
2005	A	`conf`	Fitness uniform deletion: a simple way to preserve diversity. GECCO Shane Legg, Marcus Hutter
2005	J	`jnl`	Master Algorithms for Active Experts Problems based on Increasing Loss Values CoRR Jan Poland, Marcus Hutter
2005	J	`jnl`	Monotone Conditional Complexity Bounds on Future Prediction Errors CoRR Alexey V. Chernov, Marcus Hutter
2005	B	`conf`	Monotone Conditional Complexity Bounds on Future Prediction Errors. ALT Alexey V. Chernov, Marcus Hutter
2005	J	`jnl`	On Generalized Computable Universal Priors and their Convergence CoRR Marcus Hutter
2005	J	`jnl`	Robust Inference of Trees CoRR Marco Zaffalon, Marcus Hutter
2005	J	`jnl`	Robust inference of trees. Ann. Math. Artif. Intell. Marco Zaffalon, Marcus Hutter
2005	J	`jnl`	Sequential Predictions based on Algorithmic Complexity CoRR Marcus Hutter
2005	J	`jnl`	Strong Asymptotic Assertions for Discrete MDL in Regression and Classification CoRR Jan Poland, Marcus Hutter
2005	—	`book`	Universal Artificial Intellegence - Sequential Decisions Based on Algorithmic Probability Marcus Hutter
2005	J	`jnl`	Universal Learning of Repeated Matrix Games CoRR Jan Poland, Marcus Hutter
2004	J	`jnl`	Convergence of Discrete MDL for Sequential Prediction CoRR Jan Poland, Marcus Hutter
2004	A*	`conf`	Convergence of Discrete MDL for Sequential Prediction. COLT Jan Poland, Marcus Hutter
2004	J	`jnl`	Distribution of Mutual Information from Complete and Incomplete Data CoRR Marcus Hutter, Marco Zaffalon
2004	J	`jnl`	On the Convergence Speed of MDL Predictions for Bernoulli Sequences CoRR Jan Poland, Marcus Hutter
2004	B	`conf`	On the Convergence Speed of MDL Predictions for Bernoulli Sequences. ALT Jan Poland, Marcus Hutter
2004	J	`jnl`	Prediction with Expert Advice by Following the Perturbed Leader for General Weights CoRR Marcus Hutter, Jan Poland
2004	B	`conf`	Prediction with Expert Advice by Following the Perturbed Leader for General Weights. ALT Marcus Hutter, Jan Poland
2004	J	`jnl`	Tournament versus Fitness Uniform Selection CoRR Shane Legg, Marcus Hutter, Akshat Kumar
2004	B	`conf`	Tournament versus fitness uniform selection. IEEE Congress on Evolutionary Computation Shane Legg, Marcus Hutter, Akshat Kumar
2004	J	`jnl`	Universal Convergence of Semimeasures on Individual Random Sequences CoRR Marcus Hutter, Andrej Muchnik
2004	B	`conf`	Universal Convergence of Semimeasures on Individual Random Sequences. ALT Marcus Hutter, Andrej Muchnik
2003	A*	`conf`	An Open Problem Regarding the Convergence of Universal A Priori Probability. COLT Marcus Hutter
2003	Misc	`conf`	Bayesian Treatment of Incomplete Discrete Data Applied to Mutual Information and Feature Selection. KI Marcus Hutter, Marco Zaffalon
2003	J	`jnl`	Bayesian Treatment of Incomplete Discrete Data applied to Mutual Information and Feature Selection CoRR Marcus Hutter, Marco Zaffalon
2003	J	`jnl`	Convergence and Loss Bounds for Bayesian Sequence Prediction CoRR Marcus Hutter
2003	J	`jnl`	Convergence and loss bounds for Bayesian sequence prediction. IEEE Trans. Inf. Theory Marcus Hutter
2003	J	`jnl`	Hybrid Rounding Techniques for Knapsack Problems CoRR Monaldo Mastrolilli, Marcus Hutter
2003	J	`jnl`	On the Existence and Convergence Computable Universal Priors CoRR Marcus Hutter
2003	B	`conf`	On the Existence and Convergence of Computable Universal Priors. ALT Marcus Hutter
2003	J	`jnl`	Optimal Sequential Decisions based on Algorithmic Probability CoRR Marcus Hutter
2003	J	`jnl`	Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet CoRR Marcus Hutter
2003	J	`jnl`	Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet. J. Mach. Learn. Res. Marcus Hutter
2003	—	`conf`	Robust Estimators under the Imprecise Dirichlet Model. ISIPTA Marcus Hutter
2003	A*	`conf`	Sequence Prediction Based on Monotone Complexity. COLT Marcus Hutter
2003	J	`jnl`	Sequence Prediction based on Monotone Complexity CoRR Marcus Hutter
2002	B	`conf`	Fitness uniform selection to preserve genetic diversity. IEEE Congress on Evolutionary Computation Marcus Hutter
2002	J	`jnl`	Robust Feature Selection by Mutual Information Distributions CoRR Marco Zaffalon, Marcus Hutter
2002	A	`conf`	Robust Feature Selection by Mutual Information Distributions. UAI Marco Zaffalon, Marcus Hutter
2002	A*	`conf`	Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures. COLT Marcus Hutter
2002	J	`jnl`	Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures CoRR Marcus Hutter
2002	J	`jnl`	The Fastest and Shortest Algorithm for All Well-Defined Problems CoRR Marcus Hutter
2002	J	`jnl`	The Fastest and Shortest Algorithm for all Well-Defined Problems. Int. J. Found. Comput. Sci. Marcus Hutter
2001	J	`jnl`	An effective Procedure for Speeding up Algorithms CoRR Marcus Hutter
2001	J	`jnl`	Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences CoRR Marcus Hutter
2001	—	`conf`	Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences. ECML Marcus Hutter
2001	J	`jnl`	Distribution of Mutual Information CoRR Marcus Hutter
2001	—	`conf`	Distribution of Mutual Information. NIPS Marcus Hutter
2001	J	`jnl`	Fitness Uniform Selection to Preserve Genetic Diversity CoRR Marcus Hutter
2001	J	`jnl`	General Loss Bounds for Universal Sequence Prediction CoRR Marcus Hutter
2001	A*	`conf`	General Loss Bounds for Universal Sequence Prediction. ICML Marcus Hutter
2001	J	`jnl`	Gradient-based Reinforcement Planning in Policy-Search Methods CoRR Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber
2001	J	`jnl`	Market-Based Reinforcement Learning in Partially Observable Worlds CoRR Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber
2001	C	`conf`	Market-Based Reinforcement Learning in Partially Observable Worlds. ICANN Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber
2001	J	`jnl`	New Error Bounds for Solomonoff Prediction. J. Comput. Syst. Sci. Marcus Hutter
2001	—	`conf`	Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions. ECML Marcus Hutter
2000	J	`jnl`	A Theory of Universal Artificial Intelligence based on Algorithmic Complexity CoRR Marcus Hutter
2000	J	`jnl`	Towards a Universal Theory of Artificial Intelligence based on Algorithmic Probability and Sequential Decision Theory CoRR Marcus Hutter
1999	J	`jnl`	New Error Bounds for Solomonoff Prediction CoRR Marcus Hutter