Marcus Hutter

Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann: Guest Editors' foreword. Theor. Comput. Sci. 473: 1-3 (2013)

Tor Lattimore, Marcus Hutter: On Martin-Löf Convergence of Solomonoff's Mixture. TAMC 2013: 212-223

Phuong Minh Nguyen, Peter Sunehag, Marcus Hutter: Context Tree Maximizing. AAAI 2012

Di Yang, Stephen Gould, Marcus Hutter: A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation. ACCV (1) 2012: 775-789

Peter Sunehag, Marcus Hutter: Optimistic AIXI. AGI 2012: 312-321

Joel Veness, Peter Sunehag, Marcus Hutter: On Ensemble Techniques for AIXI Approximation. AGI 2012: 341-351

Tor Lattimore, Marcus Hutter: PAC Bounds for Discounted MDPs. ALT 2012: 320-334

Peter Sunehag, Marcus Hutter: Optimistic Agents Are Asymptotically Optimal. Australasian Conference on Artificial Intelligence 2012: 15-26

Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag: Adaptive Context Tree Weighting. DCC 2012: 317-326

Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling: Context Tree Switching. DCC 2012: 327-336

Scott Sanner, Marcus Hutter (Eds.): 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

Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag: Adaptive Context Tree Weighting. CoRR abs/1201.2056 (2012)

Srimal Jayawardena, Di Yang, Marcus Hutter: 3D Model Assisted Image Segmentation. CoRR abs/1202.1943 (2012)

Tor Lattimore, Marcus Hutter: PAC Bounds for Discounted MDPs. CoRR abs/1202.3890 (2012)

Marcus Hutter: One Decade of Universal Artificial Intelligence. CoRR abs/1202.6153 (2012)

Marcus Hutter: Can Intelligence Explode? CoRR abs/1202.6177 (2012)

Joel Veness, Marcus Hutter: Sparse Sequential Dirichlet Coding. CoRR abs/1206.3618 (2012)

Marcus Hutter, John W. Lloyd, Kee Siong Ng, William T. B. Uther: Probabilities on Sentences in an Expressive Logic. CoRR abs/1209.2620 (2012)

Peter Sunehag, Marcus Hutter: Optimistic Agents are Asymptotically Optimal. CoRR abs/1210.0077 (2012)

Samuel Rathmanner, Marcus Hutter: A Philosophical Treatise of Universal Induction. Entropy 13(6): 1076-1136 (2011)

Joel Veness, Kee Siong Ng, Marcus Hutter, William T. B. Uther, David Silver: A Monte-Carlo AIXI Approximation. J. Artif. Intell. Res. (JAIR) 40: 95-142 (2011)

Tor Lattimore, Marcus Hutter, Vaibhav Gavane: Universal Prediction of Selected Bits. ALT 2011: 262-276

Peter Sunehag, Marcus Hutter: Axioms for Rational Reinforcement Learning. ALT 2011: 338-352

Tor Lattimore, Marcus Hutter: Asymptotically Optimal Agents. ALT 2011: 368-382

Tor Lattimore, Marcus Hutter: Time Consistent Discounting. ALT 2011: 383-397

Srimal Jayawardena, Marcus Hutter, Nathan Brewer: A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation. DICTA 2011: 37-44

Srimal Jayawardena, Di Yang, Marcus Hutter: 3D Model Assisted Image Segmentation. DICTA 2011: 51-58

Phuong Minh Nguyen, Peter Sunehag, Marcus Hutter: Feature Reinforcement Learning in Practice. EWRL 2011: 66-77

Marcus Hutter: Universal Learning Theory. CoRR abs/1102.2467 (2011)

Marcus Hutter: Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence. CoRR abs/1102.2468 (2011)

Samuel Rathmanner, Marcus Hutter: A Philosophical Treatise of Universal Induction. CoRR abs/1105.5721 (2011)

Peter Sunehag, Marcus Hutter: Axioms for Rational Reinforcement Learning. CoRR abs/1107.5520 (2011)

Tor Lattimore, Marcus Hutter: Time Consistent Discounting. CoRR abs/1107.5528 (2011)

Tor Lattimore, Marcus Hutter, Vaibhav Gavane: Universal Prediction of Selected Bits. CoRR abs/1107.5531 (2011)

Tor Lattimore, Marcus Hutter: Asymptotically Optimal Agents. CoRR abs/1107.5537 (2011)

Phuong Minh Nguyen, Peter Sunehag, Marcus Hutter: Feature Reinforcement Learning In Practice. CoRR abs/1108.3614 (2011)

Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling: Context Tree Switching. CoRR abs/1111.3182 (2011)

Tor Lattimore, Marcus Hutter: No Free Lunch versus Occam's Razor in Supervised Learning. CoRR abs/1111.3846 (2011)

Ian Wood, Peter Sunehag, Marcus Hutter: (Non-)Equivalence of Universal Priors. CoRR abs/1111.3854 (2011)

Peter Sunehag, Marcus Hutter: Principles of Solomonoff Induction and AIXI. CoRR abs/1111.6117 (2011)

Ben Goertzel, Marcus Hutter: Report on the Third Conference on Artificial General Intelligence. AI Magazine 31(3): 123-124 (2010)

Marcus Hutter: A Complete Theory of Everything (Will Be Subjective). Algorithms 3(4): 329-350 (2010)

Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee: An integrated Bayesian analysis of LOH and copy number data. BMC Bioinformatics 11: 321 (2010)

Marcus Hutter, Minh-Ngoc Tran: Model selection with the Loss Rank Principle. Computational Statistics & Data Analysis 54(5): 1288-1306 (2010)

Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver: Reinforcement Learning via AIXI Approximation. AAAI 2010

Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann: Editors' Introduction. ALT 2010: 1-10

Peter Sunehag, Marcus Hutter: Consistency of Feature Markov Processes. ALT 2010: 360-374

Marcus Hutter: Universal Learning Theory. Encyclopedia of Machine Learning 2010: 1001-1008

Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann (Eds.): 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

Marcus Hutter, Minh-Ngoc Tran: Model Selection with the Loss Rank Principle. CoRR abs/1003.0516 (2010)

Wray L. Buntine, Marcus Hutter: A Bayesian Review of the Poisson-Dirichlet Process. CoRR abs/1007.0296 (2010)

Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver: Reinforcement Learning via AIXI Approximation. CoRR abs/1007.2049 (2010)

Peter Sunehag, Marcus Hutter: Consistency of Feature Markov Processes. CoRR abs/1007.2075 (2010)

Srimal Jayawardena, Marcus Hutter, Nathan Brewer: Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss. CoRR abs/1011.1035 (2010)

Marcus Hutter: Open Problems in Universal Induction & Intelligence. Algorithms 2(3): 879-906 (2009)

Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee: Bayesian DNA copy number analysis. BMC Bioinformatics 10 (2009)

Marcus Hutter: Practical robust estimators for the imprecise Dirichlet model. Int. J. Approx. Reasoning 50(2): 231-242 (2009)

Alberto Piatti, Marco Zaffalon, Fabio Trojani, Marcus Hutter: Limits of learning about a categorical latent variable under prior near-ignorance. Int. J. Approx. Reasoning 50(4): 597-611 (2009)

Marcus Hutter, Rocco A. Servedio: Preface. Theor. Comput. Sci. 410(19): 1747-1748 (2009)

Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee: Bayesian Joint Estimation of CN and LOH Aberrations. IWANN (2) 2009: 1109-1117

Marcus Hutter: Discrete MDL Predicts in Total Variation. NIPS 2009: 817-825

Ke Zhang, Marcus Hutter, Huidong Jin: A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data. PAKDD 2009: 813-822

Ke Zhang, Marcus Hutter, Huidong Jin: A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data. CoRR abs/0903.3257 (2009)

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)

Marcus Hutter: Feature Reinforcement Learning: Part I: Unstructured MDPs. CoRR abs/0906.1713 (2009)

Marcus Hutter: Open Problems in Universal Induction & Intelligence. CoRR abs/0907.0746 (2009)

Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver: A Monte Carlo AIXI Approximation. CoRR abs/0909.0801 (2009)

Marcus Hutter, Nathan Brewer: Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation. CoRR abs/0912.3589 (2009)

Marcus Hutter: A Complete Theory of Everything (will be subjective). CoRR abs/0912.5434 (2009)

Daniil Ryabko, Marcus Hutter: Predicting non-stationary processes. Appl. Math. Lett. 21(5): 477-482 (2008)

Marcus Hutter: Algorithmic complexity. Scholarpedia 3(1): 2573 (2008)

Daniil Ryabko, Marcus Hutter: On the possibility of learning in reactive environments with arbitrary dependence. Theor. Comput. Sci. 405(3): 274-284 (2008)

Kassel Hingee, Marcus Hutter: Equivalence of probabilistic tournament and polynomial ranking selection. IEEE Congress on Evolutionary Computation 2008: 564-571

Kassel Hingee, Marcus Hutter: Equivalence of Probabilistic Tournament and Polynomial Ranking Selection. CoRR abs/0803.2925 (2008)

Marcus Hutter: Predictive Hypothesis Identification. CoRR abs/0809.1270 (2008)

Marcus Hutter, Shane Legg: Temporal Difference Updating without a Learning Rate. CoRR abs/0810.5631 (2008)

Daniil Ryabko, Marcus Hutter: On the Possibility of Learning in Reactive Environments with Arbitrary Dependence. CoRR abs/0810.5636 (2008)

Marcus Hutter: Feature Markov Decision Processes. CoRR abs/0812.4580 (2008)

Marcus Hutter: Feature Dynamic Bayesian Networks. CoRR abs/0812.4581 (2008)

Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Algorithmic complexity bounds on future prediction errors. Inf. Comput. 205(2): 242-261 (2007)

Shane Legg, Marcus Hutter: Universal Intelligence: A Definition of Machine Intelligence. Minds and Machines 17(4): 391-444 (2007)

Marcus Hutter: Algorithmic information theory. Scholarpedia 2(3): 2519 (2007)

Marcus Hutter, Shane Legg, Paul M. B. Vitányi: Algorithmic probability. Scholarpedia 2(8): 2572 (2007)

Marcus Hutter, Andrej Muchnik: On semimeasures predicting Martin-Löf random sequences. Theor. Comput. Sci. 382(3): 247-261 (2007)

Marcus Hutter: On universal prediction and Bayesian confirmation. Theor. Comput. Sci. 384(1): 33-48 (2007)

Marcus Hutter, Rocco A. Servedio, Eiji Takimoto: Editors' Introduction. ALT 2007: 1-8

Marcus Hutter: The Loss Rank Principle for Model Selection. COLT 2007: 589-603

Marcus Hutter, Shane Legg: Temporal Difference Updating without a Learning Rate. NIPS 2007

Marcus Hutter, Rocco A. Servedio, Eiji Takimoto (Eds.): 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

Shane Legg, Marcus Hutter: A Collection of Definitions of Intelligence. CoRR abs/0706.3639 (2007)

Marcus Hutter, Andrej Muchnik: On Semimeasures Predicting Martin-Loef Random Sequences. CoRR abs/0708.2319 (2007)

Marcus Hutter: On Universal Prediction and Bayesian Confirmation. CoRR abs/0709.1516 (2007)

Shane Legg, Marcus Hutter: Universal Intelligence: A Definition of Machine Intelligence. CoRR abs/0712.3329 (2007)

Shane Legg, Marcus Hutter: Tests of Machine Intelligence. CoRR abs/0712.3825 (2007)

Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Algorithmic Complexity Bounds on Future Prediction Errors. CoRR abs/cs/0701120 (2007)

Marcus Hutter: Universal Algorithmic Intelligence: A mathematical top->down approach. CoRR abs/cs/0701125 (2007)

Marcus Hutter: Algorithmic Information Theory: a brief non-technical guide to the field. CoRR abs/cs/0703024 (2007)

Marcus Hutter: The Loss Rank Principle for Model Selection. CoRR abs/math/0702804 (2007)

Monaldo Mastrolilli, Marcus Hutter: Hybrid rounding techniques for knapsack problems. Discrete Applied Mathematics 154(4): 640-649 (2006)

Marcus Hutter: Sequential predictions based on algorithmic complexity. J. Comput. Syst. Sci. 72(1): 95-117 (2006)

Jan Poland, Marcus Hutter: MDL convergence speed for Bernoulli sequences. Statistics and Computing 16(2): 161-175 (2006)

Marcus Hutter: On generalized computable universal priors and their convergence. Theor. Comput. Sci. 364(1): 27-41 (2006)

Marcus Hutter, Shane Legg: Fitness uniform optimization. IEEE Trans. Evolutionary Computation 10(5): 568-589 (2006)

Shane Legg, Marcus Hutter: Tests of Machine Intelligence. 50 Years of Artificial Intelligence 2006: 232-242

Marcus Hutter: General Discounting Versus Average Reward. ALT 2006: 244-258

Daniil Ryabko, Marcus Hutter: Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence. ALT 2006: 334-347

Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Complexity Monotone in Conditions and Future Prediction Errors. Kolmogorov Complexity and Applications 2006

Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi: 06051 Abstracts Collection -- Kolmogorov Complexity and Applications. Kolmogorov Complexity and Applications 2006

Daniil Ryabko, Marcus Hutter: Sequence prediction for non-stationary processes. Combinatorial and Algorithmic Foundations of Pattern and Association Discovery 2006

Daniil Ryabko, Marcus Hutter: Learning in Reactive Environments with Arbitrary Dependence. Kolmogorov Complexity and Applications 2006

Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber: Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot. IAS 2006: 272-281

Marcus Hutter: On the Foundations of Universal Sequence Prediction. TAMC 2006: 408-420

Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi (Eds.): Kolmogorov Complexity and Applications, 29.01. - 03.02.2006. Dagstuhl Seminar Proceedings 06051, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2006

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)

Daniil Ryabko, Marcus Hutter: Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence. CoRR abs/cs/0603110 (2006)

Marcus Hutter: On the Foundations of Universal Sequence Prediction. CoRR abs/cs/0605009 (2006)

Shane Legg, Marcus Hutter: A Formal Measure of Machine Intelligence. CoRR abs/cs/0605024 (2006)

Marcus Hutter: General Discounting versus Average Reward. CoRR abs/cs/0605040 (2006)

Daniil Ryabko, Marcus Hutter: On Sequence Prediction for Arbitrary Measures. CoRR abs/cs/0606077 (2006)

Marcus Hutter, Shane Legg: Fitness Uniform Optimization. CoRR abs/cs/0610126 (2006)

Jan Poland, Marcus Hutter: MDL Convergence Speed for Bernoulli Sequences. CoRR abs/math/0602505 (2006)

Marcus Hutter: Bayesian Regression of Piecewise Constant Functions. CoRR abs/math/0606315 (2006)

Marco Zaffalon, Marcus Hutter: Robust inference of trees. Ann. Math. Artif. Intell. 45(1-2): 215-239 (2005)

Marcus Hutter, Marco Zaffalon: Distribution of mutual information from complete and incomplete data. Computational Statistics & Data Analysis 48(3): 633-657 (2005)

Marcus Hutter, Jan Poland: Adaptive Online Prediction by Following the Perturbed Leader. Journal of Machine Learning Research 6: 639-660 (2005)

Jan Poland, Marcus Hutter: Asymptotics of discrete MDL for online prediction. IEEE Transactions on Information Theory 51(11): 3780-3795 (2005)

Jan Poland, Marcus Hutter: Defensive Universal Learning with Experts. ALT 2005: 356-370

Alexey V. Chernov, Marcus Hutter: Monotone Conditional Complexity Bounds on Future Prediction Errors. ALT 2005: 414-428

Shane Legg, Marcus Hutter: Fitness uniform deletion: a simple way to preserve diversity. GECCO 2005: 1271-1278

Shane Legg, Marcus Hutter: A Universal Measure of Intelligence for Artificial Agents. IJCAI 2005: 1509-1510

Jan Poland, Marcus Hutter: Master Algorithms for Active Experts Problems based on Increasing Loss Values. CoRR abs/cs/0502067 (2005)

Marcus Hutter: On Generalized Computable Universal Priors and their Convergence. CoRR abs/cs/0503026 (2005)

Shane Legg, Marcus Hutter: Fitness Uniform Deletion: A Simple Way to Preserve Diversity. CoRR abs/cs/0504035 (2005)

Marcus Hutter, Jan Poland: Adaptive Online Prediction by Following the Perturbed Leader. CoRR abs/cs/0504078 (2005)

Jan Poland, Marcus Hutter: Asymptotics of Discrete MDL for Online Prediction. CoRR abs/cs/0506022 (2005)

Alexey V. Chernov, Marcus Hutter: Monotone Conditional Complexity Bounds on Future Prediction Errors. CoRR abs/cs/0507041 (2005)

Jan Poland, Marcus Hutter: Defensive Universal Learning with Experts. CoRR abs/cs/0507044 (2005)

Marcus Hutter: Sequential Predictions based on Algorithmic Complexity. CoRR abs/cs/0508043 (2005)

Jan Poland, Marcus Hutter: Universal Learning of Repeated Matrix Games. CoRR abs/cs/0508073 (2005)

Marco Zaffalon, Marcus Hutter: Robust Inference of Trees. CoRR abs/cs/0511087 (2005)

Jan Poland, Marcus Hutter: Strong Asymptotic Assertions for Discrete MDL in Regression and Classification. CoRR abs/math/0502315 (2005)

Marcus Hutter, Andrej Muchnik: Universal Convergence of Semimeasures on Individual Random Sequences. ALT 2004: 234-248

Marcus Hutter, Jan Poland: Prediction with Expert Advice by Following the Perturbed Leader for General Weights. ALT 2004: 279-293

Jan Poland, Marcus Hutter: On the Convergence Speed of MDL Predictions for Bernoulli Sequences. ALT 2004: 294-308

Jan Poland, Marcus Hutter: Convergence of Discrete MDL for Sequential Prediction. COLT 2004: 300-314

Marcus Hutter, Marco Zaffalon: Distribution of Mutual Information from Complete and Incomplete Data. CoRR cs.LG/0403025 (2004)

Shane Legg, Marcus Hutter, Akshat Kumar: Tournament versus Fitness Uniform Selection. CoRR cs.LG/0403038 (2004)

Jan Poland, Marcus Hutter: Convergence of Discrete MDL for Sequential Prediction. CoRR cs.LG/0404057 (2004)

Marcus Hutter, Jan Poland: Prediction with Expert Advice by Following the Perturbed Leader for General Weights. CoRR cs.LG/0405043 (2004)

Jan Poland, Marcus Hutter: On the Convergence Speed of MDL Predictions for Bernoulli Sequences. CoRR cs.LG/0407039 (2004)

Marcus Hutter, Andrej Muchnik: Universal Convergence of Semimeasures on Individual Random Sequences. CoRR cs.LG/0407057 (2004)

Marcus Hutter: Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet. Journal of Machine Learning Research 4: 971-1000 (2003)

Marcus Hutter: Convergence and loss bounds for Bayesian sequence prediction. IEEE Transactions on Information Theory 49(8): 2061-2067 (2003)

Marcus Hutter: On the Existence and Convergence of Computable Universal Priors. ALT 2003: 298-312

Marcus Hutter: Sequence Prediction Based on Monotone Complexity. COLT 2003: 506-521

Marcus Hutter: An Open Problem Regarding the Convergence of Universal A Priori Probability. COLT 2003: 738-740

Marcus Hutter: Robust Estimators under the Imprecise Dirichlet Model. ISIPTA 2003: 274-289

Marcus Hutter, Marco Zaffalon: Bayesian Treatment of Incomplete Discrete Data Applied to Mutual Information and Feature Selection. KI 2003: 396-406

Marcus Hutter: Sequence Prediction based on Monotone Complexity. CoRR cs.AI/0306036 (2003)

Marcus Hutter: Optimal Sequential Decisions based on Algorithmic Probability. CoRR cs.AI/0306091 (2003)

Monaldo Mastrolilli, Marcus Hutter: Hybrid Rounding Techniques for Knapsack Problems. CoRR cs.CC/0305002 (2003)

Marcus Hutter: Convergence and Loss Bounds for Bayesian Sequence Prediction. CoRR cs.LG/0301014 (2003)

Marcus Hutter: On the Existence and Convergence Computable Universal Priors. CoRR cs.LG/0305052 (2003)

Marcus Hutter, Marco Zaffalon: Bayesian Treatment of Incomplete Discrete Data applied to Mutual Information and Feature Selection. CoRR cs.LG/0306126 (2003)

Marcus Hutter: Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet. CoRR cs.LG/0311014 (2003)

Marcus Hutter: The Fastest and Shortest Algorithm for all Well-Defined Problems. Int. J. Found. Comput. Sci. 13(3): 431-443 (2002)

Marcus Hutter: Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures. COLT 2002: 364-379

Marco Zaffalon, Marcus Hutter: Robust Feature Selection by Mutual Information Distributions. UAI 2002: 577-584

Marcus Hutter: Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures. CoRR cs.AI/0204040 (2002)

Marco Zaffalon, Marcus Hutter: Robust Feature Selection by Mutual Information Distributions. CoRR cs.AI/0206006 (2002)

Marcus Hutter: The Fastest and Shortest Algorithm for All Well-Defined Problems. CoRR cs.CC/0206022 (2002)

Marcus Hutter: New Error Bounds for Solomonoff Prediction. J. Comput. Syst. Sci. 62(4): 653-667 (2001)

Marcus Hutter: Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions. ECML 2001: 226-238

Marcus Hutter: Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences. ECML 2001: 239-250

Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Market-Based Reinforcement Learning in Partially Observable Worlds. ICANN 2001: 865-873

Marcus Hutter: General Loss Bounds for Universal Sequence Prediction. ICML 2001: 210-217

Marcus Hutter: Distribution of Mutual Information. NIPS 2001: 399-406

Marcus Hutter: General Loss Bounds for Universal Sequence Prediction. CoRR cs.AI/0101019 (2001)

Marcus Hutter: Fitness Uniform Selection to Preserve Genetic Diversity. CoRR cs.AI/0103015 (2001)

Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Market-Based Reinforcement Learning in Partially Observable Worlds. CoRR cs.AI/0105025 (2001)

Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Gradient-based Reinforcement Planning in Policy-Search Methods. CoRR cs.AI/0111060 (2001)

Marcus Hutter: Distribution of Mutual Information. CoRR cs.AI/0112019 (2001)

Marcus Hutter: An effective Procedure for Speeding up Algorithms. CoRR cs.CC/0102018 (2001)

Marcus Hutter: Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences. CoRR cs.LG/0106036 (2001)

Marcus Hutter: A Theory of Universal Artificial Intelligence based on Algorithmic Complexity. CoRR cs.AI/0004001 (2000)

Marcus Hutter: Towards a Universal Theory of Artificial Intelligence based on Algorithmic Probability and Sequential Decision Theory. CoRR cs.AI/0012011 (2000)

Marcus Hutter: New Error Bounds for Solomonoff Prediction. CoRR cs.AI/9912008 (1999)