Marcus Hutter
According to our database^{1},
Marcus Hutter
authored at least 154 papers
between 2001 and 2018.
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Bibliography
2018
On the computability of Solomonoff induction and AIXI.
Theor. Comput. Sci., 2018
Tractability of batch to sequential conversion.
Theor. Comput. Sci., 2018
Convergence of Binarized Contexttree Weighting for Estimating Distributions of Stationary Sources.
Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018
On Qlearning Convergence for NonMarkov Decision Processes.
Proceedings of the TwentySeventh International Joint Conference on Artificial Intelligence, 2018
AGI Safety Literature Review.
Proceedings of the TwentySeventh International Joint Conference on Artificial Intelligence, 2018
Universal Compression of Piecewise i.i.d. Sources.
Proceedings of the 2018 Data Compression Conference, 2018
2017
Universal Learning Theory.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017
CountBased Exploration in Feature Space for Reinforcement Learning.
Proceedings of the TwentySixth International Joint Conference on Artificial Intelligence, 2017
On Thompson Sampling and Asymptotic Optimality.
Proceedings of the TwentySixth International Joint Conference on Artificial Intelligence, 2017
Universal Reinforcement Learning Algorithms: Survey and Experiments.
Proceedings of the TwentySixth International Joint Conference on Artificial Intelligence, 2017
Generalised Discount Functions applied to a MonteCarlo AI u Implementation.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017
A GameTheoretic Analysis of the OffSwitch Game.
Proceedings of the Artificial General Intelligence  10th International Conference, 2017
2016
Extreme state aggregation beyond Markov decision processes.
Theor. Comput. Sci., 2016
Thompson Sampling is Asymptotically Optimal in General Environments.
Proceedings of the ThirtySecond Conference on Uncertainty in Artificial Intelligence, 2016
Discriminative Hierarchical Rank Pooling for Activity Recognition.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016
Loss Bounds and Time Complexity for Speed Priors.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
Death and Suicide in Universal Artificial Intelligence.
Proceedings of the Artificial General Intelligence  9th International Conference, 2016
Avoiding Wireheading with Value Reinforcement Learning.
Proceedings of the Artificial General Intelligence  9th International Conference, 2016
SelfModification of Policy and Utility Function in Rational Agents.
Proceedings of the Artificial General Intelligence  9th International Conference, 2016
2015
On MartinLöf (non)convergence of Solomonoff's universal mixture.
Theor. Comput. Sci., 2015
Rationality, optimism and guarantees in general reinforcement learning.
Journal of Machine Learning Research, 2015
On the Computability of AIXI.
Proceedings of the ThirtyFirst Conference on Uncertainty in Artificial Intelligence, 2015
Online Learning of kCNF Boolean Functions.
Proceedings of the TwentyFourth International Joint Conference on Artificial Intelligence, 2015
Bad Universal Priors and Notions of Optimality.
Proceedings of The 28th Conference on Learning Theory, 2015
Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search.
Proceedings of the AI 2015: Advances in Artificial Intelligence, 2015
Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search.
Proceedings of the AI 2015: Advances in Artificial Intelligence, 2015
On the Computability of Solomonoff Induction and KnowledgeSeeking.
Proceedings of the Algorithmic Learning Theory  26th International Conference, 2015
Solomonoff Induction Violates Nicod's Criterion.
Proceedings of the Algorithmic Learning Theory  26th International Conference, 2015
Sequential Extensions of Causal and Evidential Decision Theory.
Proceedings of the Algorithmic Decision Theory  4th International Conference, 2015
Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning.
Proceedings of the Artificial General Intelligence, 2015
Compress and Control.
Proceedings of the TwentyNinth AAAI Conference on Artificial Intelligence, 2015
2014
Nearoptimal PAC bounds for discounted MDPs.
Theor. Comput. Sci., 2014
General time consistent discounting.
Theor. Comput. Sci., 2014
Can we measure the difficulty of an optimization problem?
Proceedings of the 2014 IEEE Information Theory Workshop, 2014
Reflective Features Detection and Hierarchical Reflections Separation in Image Sequences.
Proceedings of the 2014 International Conference on Digital Image Computing: Techniques and Applications, 2014
A Dual Process Theory of Optimistic Cognition.
Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014
Free Lunch for optimisation under the universal distribution.
Proceedings of the IEEE Congress on Evolutionary Computation, 2014
Indefinitely Oscillating Martingales.
Proceedings of the Algorithmic Learning Theory  25th International Conference, 2014
Bayesian Reinforcement Learning with Exploration.
Proceedings of the Algorithmic Learning Theory  25th International Conference, 2014
Offline to Online Conversion.
Proceedings of the Algorithmic Learning Theory  25th International Conference, 2014
Extreme State Aggregation beyond MDPs.
Proceedings of the Algorithmic Learning Theory  25th International Conference, 2014
Intelligence as Inference or Forcing Occam on the World.
Proceedings of the Artificial General Intelligence  7th International Conference, 2014
Reinforcement learning with value advice.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014
Reliable Point Correspondences in Scenes Dominated by Highly Reflective and Largely Homogeneous Surfaces.
Proceedings of the Computer Vision  ACCV 2014 Workshops, 2014
2013
Guest Editors' foreword.
Theor. Comput. Sci., 2013
Probabilities on Sentences in an Expressive Logic.
J. Applied Logic, 2013
Reinforcement Learning (Dagstuhl Seminar 13321).
Dagstuhl Reports, 2013
On MartinLöf Convergence of Solomonoff's Mixture.
Proceedings of the Theory and Applications of Models of Computation, 2013
The SampleComplexity of General Reinforcement Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013
Sparse Adaptive DirichletMultinomiallike Processes.
Proceedings of the COLT 2013, 2013
Universal KnowledgeSeeking Agents for Stochastic Environments.
Proceedings of the Algorithmic Learning Theory  24th International Conference, 2013
Concentration and Confidence for Discrete Bayesian Sequence Predictors.
Proceedings of the Algorithmic Learning Theory  24th International Conference, 2013
Learning Agents with Evolving Hypothesis Classes.
Proceedings of the Artificial General Intelligence  6th International Conference, 2013
Qlearning for historybased reinforcement learning.
Proceedings of the Asian Conference on Machine Learning, 2013
2012
Feature Reinforcement Learning using Looping Suffix Trees.
Proceedings of the Tenth European Workshop on Reinforcement Learning, 2012
Context Tree Switching.
Proceedings of the 2012 Data Compression Conference, Snowbird, UT, USA, April 1012, 2012, 2012
Adaptive Context Tree Weighting.
Proceedings of the 2012 Data Compression Conference, Snowbird, UT, USA, April 1012, 2012, 2012
Coding of NonStationary Sources as a Foundation for Detecting Change Points and Outliers in Binary TimeSeries.
Proceedings of the Tenth Australasian Data Mining Conference, AusDM 2012, Sydney, 2012
Optimistic Agents Are Asymptotically Optimal.
Proceedings of the AI 2012: Advances in Artificial Intelligence, 2012
PAC Bounds for Discounted MDPs.
Proceedings of the Algorithmic Learning Theory  23rd International Conference, 2012
On Ensemble Techniques for AIXI Approximation.
Proceedings of the Artificial General Intelligence  5th International Conference, 2012
Optimistic AIXI.
Proceedings of the Artificial General Intelligence  5th International Conference, 2012
A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation.
Proceedings of the Computer Vision  ACCV 2012, 2012
Context Tree Maximizing.
Proceedings of the TwentySixth AAAI Conference on Artificial Intelligence, 2012
2011
A MonteCarlo AIXI Approximation.
J. Artif. Intell. Res., 2011
A Philosophical Treatise of Universal Induction.
Entropy, 2011
Feature Reinforcement Learning in Practice.
Proceedings of the Recent Advances in Reinforcement Learning  9th European Workshop, 2011
3D Model Assisted Image Segmentation.
Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2011
A Novel IlluminationInvariant Loss for Monocular 3D Pose Estimation.
Proceedings of the 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2011
(Non)Equivalence of Universal Priors.
Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011
Principles of Solomonoff Induction and AIXI.
Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011
No Free Lunch versus Occam's Razor in Supervised Learning.
Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011
Axioms for Rational Reinforcement Learning.
Proceedings of the Algorithmic Learning Theory  22nd International Conference, 2011
Universal Prediction of Selected Bits.
Proceedings of the Algorithmic Learning Theory  22nd International Conference, 2011
Time Consistent Discounting.
Proceedings of the Algorithmic Learning Theory  22nd International Conference, 2011
Asymptotically Optimal Agents.
Proceedings of the Algorithmic Learning Theory  22nd International Conference, 2011
2010
Universal Learning Theory.
Proceedings of the Encyclopedia of Machine Learning, 2010
Model selection with the Loss Rank Principle.
Computational Statistics & Data Analysis, 2010
An integrated Bayesian analysis of LOH and copy number data.
BMC Bioinformatics, 2010
A Complete Theory of Everything (Will Be Subjective).
Algorithms, 2010
Report on the Third Conference on Artificial General Intelligence.
AI Magazine, 2010
Consistency of Feature Markov Processes.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010
Editors' Introduction.
Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010
Reinforcement Learning via AIXI Approximation.
Proceedings of the TwentyFourth AAAI Conference on Artificial Intelligence, 2010
2009
Preface.
Theor. Comput. Sci., 2009
Feature Reinforcement Learning: Part I. Unstructured MDPs.
J. Artificial General Intelligence, 2009
Limits of learning about a categorical latent variable under prior nearignorance.
Int. J. Approx. Reasoning, 2009
Practical robust estimators for the imprecise Dirichlet model.
Int. J. Approx. Reasoning, 2009
Bayesian DNA copy number analysis.
BMC Bioinformatics, 2009
Open Problems in Universal Induction & Intelligence.
Algorithms, 2009
A New Local DistanceBased Outlier Detection Approach for Scattered RealWorld Data.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2009
Discrete MDL Predicts in Total Variation.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
Bayesian Joint Estimation of CN and LOH Aberrations.
Proceedings of the Distributed Computing, 2009
2008
On the possibility of learning in reactive environments with arbitrary dependence.
Theor. Comput. Sci., 2008
Algorithmic complexity.
Scholarpedia, 2008
Predicting nonstationary processes.
Appl. Math. Lett., 2008
Equivalence of probabilistic tournament and polynomial ranking selection.
Proceedings of the IEEE Congress on Evolutionary Computation, 2008
2007
Universal Algorithmic Intelligence: A Mathematical Top→Down Approach.
Proceedings of the Artificial General Intelligence, 2007
On semimeasures predicting MartinLöf random sequences.
Theor. Comput. Sci., 2007
On universal prediction and Bayesian confirmation.
Theor. Comput. Sci., 2007
Algorithmic probability.
Scholarpedia, 2007
Algorithmic information theory.
Scholarpedia, 2007
Universal Intelligence: A Definition of Machine Intelligence.
Minds and Machines, 2007
Algorithmic complexity bounds on future prediction errors.
Inf. Comput., 2007
Temporal Difference Updating without a Learning Rate.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
On Sequence Prediction for Arbitrary Measures.
Proceedings of the IEEE International Symposium on Information Theory, 2007
The Loss Rank Principle for Model Selection.
Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007
Editors' Introduction.
Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007
2006
Fitness uniform optimization.
IEEE Trans. Evolutionary Computation, 2006
On generalized computable universal priors and their convergence.
Theor. Comput. Sci., 2006
MDL convergence speed for Bernoulli sequences.
Statistics and Computing, 2006
Sequential predictions based on algorithmic complexity.
J. Comput. Syst. Sci., 2006
Hybrid rounding techniques for knapsack problems.
Discrete Applied Mathematics, 2006
On the Foundations of Universal Sequence Prediction.
Proceedings of the Theory and Applications of Models of Computation, 2006
Metric State Space Reinforcement Learning for a VisionCapable Mobile Robot.
Proceedings of the Intelligent Autonomous Systems 9, 2006
Learning in Reactive Environments with Arbitrary Dependence.
Proceedings of the Kolmogorov Complexity and Applications, 29.01.  03.02.2006, 2006
Sequence prediction for nonstationary processes.
Proceedings of the Combinatorial and Algorithmic Foundations of Pattern and Association Discovery, 14.05., 2006
06051 Abstracts Collection  Kolmogorov Complexity and Applications.
Proceedings of the Kolmogorov Complexity and Applications, 29.01.  03.02.2006, 2006
Complexity Monotone in Conditions and Future Prediction Errors.
Proceedings of the Kolmogorov Complexity and Applications, 29.01.  03.02.2006, 2006
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006
General Discounting Versus Average Reward.
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006
Tests of Machine Intelligence.
Proceedings of the 50 Years of Artificial Intelligence, 2006
A Collection of Definitions of Intelligence.
Proceedings of the Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms, 2006
2005
Universal Artificial Intellegence  Sequential Decisions Based on Algorithmic Probability
Texts in Theoretical Computer Science. An EATCS Series, Springer, ISBN: 9783540268772, 2005
Asymptotics of discrete MDL for online prediction.
IEEE Trans. Information Theory, 2005
Adaptive Online Prediction by Following the Perturbed Leader.
Journal of Machine Learning Research, 2005
Distribution of mutual information from complete and incomplete data.
Computational Statistics & Data Analysis, 2005
Robust inference of trees.
Ann. Math. Artif. Intell., 2005
A Universal Measure of Intelligence for Artificial Agents.
Proceedings of the IJCAI05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005
Fitness uniform deletion: a simple way to preserve diversity.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005
Defensive Universal Learning with Experts.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005
Monotone Conditional Complexity Bounds on Future Prediction Errors.
Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005
Fast NonParametric Bayesian Inference on Infinite Trees.
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005
2004
Convergence of Discrete MDL for Sequential Prediction.
Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004
Tournament versus fitness uniform selection.
Proceedings of the IEEE Congress on Evolutionary Computation, 2004
On the Convergence Speed of MDL Predictions for Bernoulli Sequences.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004
Prediction with Expert Advice by Following the Perturbed Leader for General Weights.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004
Universal Convergence of Semimeasures on Individual Random Sequences.
Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004
2003
Convergence and loss bounds for Bayesian sequence prediction.
IEEE Trans. Information Theory, 2003
Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet.
Journal of Machine Learning Research, 2003
Bayesian Treatment of Incomplete Discrete Data Applied to Mutual Information and Feature Selection.
Proceedings of the KI 2003: Advances in Artificial Intelligence, 2003
Robust Estimators under the Imprecise Dirichlet Model.
Proceedings of the ISIPTA '03, 2003
An Open Problem Regarding the Convergence of Universal A Priori Probability.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003
Sequence Prediction Based on Monotone Complexity.
Proceedings of the Computational Learning Theory and Kernel Machines, 2003
On the Existence and Convergence of Computable Universal Priors.
Proceedings of the Algorithmic Learning Theory, 14th International Conference, 2003
2002
The Fastest and Shortest Algorithm for all WellDefined Problems.
Int. J. Found. Comput. Sci., 2002
Robust Feature Selection by Mutual Information Distributions.
Proceedings of the UAI '02, 2002
SelfOptimizing and ParetoOptimal Policies in General Environments Based on BayesMixtures.
Proceedings of the Computational Learning Theory, 2002
2001
New Error Bounds for Solomonoff Prediction.
J. Comput. Syst. Sci., 2001
Distribution of Mutual Information.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001
General Loss Bounds for Universal Sequence Prediction.
Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001
MarketBased Reinforcement Learning in Partially Observable Worlds.
Proceedings of the Artificial Neural Networks, 2001
Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences.
Proceedings of the Machine Learning: EMCL 2001, 2001
Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions.
Proceedings of the Machine Learning: EMCL 2001, 2001