Marcus Hutter

	2012
175		Scott Sanner, Marcus Hutter: Recent Advances in Reinforcement Learning - 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised Selected Papers Springer 2012
174		Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag: Adaptive Context Tree Weighting. DCC 2012: 317-326
173		Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling: Context Tree Switching. DCC 2012: 327-336
172		Alexander O'Neill, Marcus Hutter, Wen Shao, Peter Sunehag: Adaptive Context Tree Weighting CoRR abs/1201.2056: (2012)
171		Srimal Jayawardena, Di Yang, Marcus Hutter: 3D Model Assisted Image Segmentation CoRR abs/1202.1943: (2012)
170		Tor Lattimore, Marcus Hutter: PAC Bounds for Discounted MDPs CoRR abs/1202.3890: (2012)
169		Marcus Hutter: One Decade of Universal Artificial Intelligence CoRR abs/1202.6153: (2012)
168		Marcus Hutter: Can Intelligence Explode? CoRR abs/1202.6177: (2012)
	2011
167		Tor Lattimore, Marcus Hutter, Vaibhav Gavane: Universal Prediction of Selected Bits. ALT 2011: 262-276
166		Peter Sunehag, Marcus Hutter: Axioms for Rational Reinforcement Learning. ALT 2011: 338-352
165		Tor Lattimore, Marcus Hutter: Asymptotically Optimal Agents. ALT 2011: 368-382
164		Tor Lattimore, Marcus Hutter: Time Consistent Discounting. ALT 2011: 383-397
163		Srimal Jayawardena, Marcus Hutter, Nathan Brewer: A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation. DICTA 2011: 37-44
162		Srimal Jayawardena, Di Yang, Marcus Hutter: 3D Model Assisted Image Segmentation. DICTA 2011: 51-58
161		Phuong Nguyen, Peter Sunehag, Marcus Hutter: Feature Reinforcement Learning in Practice. EWRL 2011: 66-77
160		Marcus Hutter: Universal Learning Theory CoRR abs/1102.2467: (2011)
159		Marcus Hutter: Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence CoRR abs/1102.2468: (2011)
158		Samuel Rathmanner, Marcus Hutter: A Philosophical Treatise of Universal Induction CoRR abs/1105.5721: (2011)
157		Peter Sunehag, Marcus Hutter: Axioms for Rational Reinforcement Learning CoRR abs/1107.5520: (2011)
156		Tor Lattimore, Marcus Hutter: Time Consistent Discounting CoRR abs/1107.5528: (2011)
155		Tor Lattimore, Marcus Hutter, Vaibhav Gavane: Universal Prediction of Selected Bits CoRR abs/1107.5531: (2011)
154		Tor Lattimore, Marcus Hutter: Asymptotically Optimal Agents CoRR abs/1107.5537: (2011)
153		Phuong Nguyen, Peter Sunehag, Marcus Hutter: Feature Reinforcement Learning In Practice CoRR abs/1108.3614: (2011)
152		Joel Veness, Kee Siong Ng, Marcus Hutter, Michael H. Bowling: Context Tree Switching CoRR abs/1111.3182: (2011)
151		Tor Lattimore, Marcus Hutter: No Free Lunch versus Occam's Razor in Supervised Learning CoRR abs/1111.3846: (2011)
150		Ian Wood, Peter Sunehag, Marcus Hutter: (Non-)Equivalence of Universal Priors CoRR abs/1111.3854: (2011)
149		Peter Sunehag, Marcus Hutter: Principles of Solomonoff Induction and AIXI CoRR abs/1111.6117: (2011)
148		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)
	2010
147		Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann: Algorithmic Learning Theory, 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings Springer 2010
146		Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver: Reinforcement Learning via AIXI Approximation. AAAI 2010
145		Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmann: Editors' Introduction. ALT 2010: 1-10
144		Peter Sunehag, Marcus Hutter: Consistency of Feature Markov Processes. ALT 2010: 360-374
143		Marcus Hutter: Universal Learning Theory. Encyclopedia of Machine Learning 2010: 1001-1008
142		Ben Goertzel, Marcus Hutter: Report on the Third Conference on Artificial General Intelligence. AI Magazine 31(3): 123-124 (2010)
141		Marcus Hutter: A Complete Theory of Everything (Will Be Subjective). Algorithms 3(4): 329-350 (2010)
140		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)
139		Marcus Hutter, Minh-Ngoc Tran: Model Selection with the Loss Rank Principle CoRR abs/1003.0516: (2010)
138		Wray L. Buntine, Marcus Hutter: A Bayesian Review of the Poisson-Dirichlet Process CoRR abs/1007.0296: (2010)
137		Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver: Reinforcement Learning via AIXI Approximation CoRR abs/1007.2049: (2010)
136		Peter Sunehag, Marcus Hutter: Consistency of Feature Markov Processes CoRR abs/1007.2075: (2010)
135		Srimal Jayawardena, Marcus Hutter, Nathan Brewer: Featureless 2D-3D Pose Estimation by Minimising an Illumination-Invariant Loss CoRR abs/1011.1035: (2010)
134		Marcus Hutter, Minh-Ngoc Tran: Model selection with the Loss Rank Principle. Computational Statistics & Data Analysis 54(5): 1288-1306 (2010)
	2009
133		Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee: Bayesian Joint Estimation of CN and LOH Aberrations. IWANN (2) 2009: 1109-1117
132		Marcus Hutter: Discrete MDL Predicts in Total Variation. NIPS 2009: 817-825
131		Ke Zhang, Marcus Hutter, Huidong Jin: A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data. PAKDD 2009: 813-822
130		Marcus Hutter: Open Problems in Universal Induction & Intelligence. Algorithms 2(3): 879-906 (2009)
129		Paola M. V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee: Bayesian DNA copy number analysis. BMC Bioinformatics 10: (2009)
128		Ke Zhang, Marcus Hutter, Huidong Jin: A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data CoRR abs/0903.3257: (2009)
127		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)
126		Marcus Hutter: Feature Reinforcement Learning: Part I: Unstructured MDPs CoRR abs/0906.1713: (2009)
125		Marcus Hutter: Open Problems in Universal Induction & Intelligence CoRR abs/0907.0746: (2009)
124		Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver: A Monte Carlo AIXI Approximation CoRR abs/0909.0801: (2009)
123		Marcus Hutter, Nathan Brewer: Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation CoRR abs/0912.3589: (2009)
122		Marcus Hutter: A Complete Theory of Everything (will be subjective) CoRR abs/0912.5434: (2009)
121		Marcus Hutter: Practical robust estimators for the imprecise Dirichlet model. Int. J. Approx. Reasoning 50(2): 231-242 (2009)
120		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)
119		Marcus Hutter, Rocco A. Servedio: Preface. Theor. Comput. Sci. 410(19): 1747-1748 (2009)
	2008
118		Kassel Hingee, Marcus Hutter: Equivalence of probabilistic tournament and polynomial ranking selection. IEEE Congress on Evolutionary Computation 2008: 564-571
117		Daniil Ryabko, Marcus Hutter: Predicting non-stationary processes. Appl. Math. Lett. 21(5): 477-482 (2008)
116		Kassel Hingee, Marcus Hutter: Equivalence of Probabilistic Tournament and Polynomial Ranking Selection CoRR abs/0803.2925: (2008)
115		Marcus Hutter: Predictive Hypothesis Identification CoRR abs/0809.1270: (2008)
114		Marcus Hutter, Shane Legg: Temporal Difference Updating without a Learning Rate CoRR abs/0810.5631: (2008)
113		Daniil Ryabko, Marcus Hutter: On the Possibility of Learning in Reactive Environments with Arbitrary Dependence CoRR abs/0810.5636: (2008)
112		Marcus Hutter: Feature Markov Decision Processes CoRR abs/0812.4580: (2008)
111		Marcus Hutter: Feature Dynamic Bayesian Networks CoRR abs/0812.4581: (2008)
110		Marcus Hutter: Algorithmic complexity. Scholarpedia 3(1): 2573 (2008)
109		Daniil Ryabko, Marcus Hutter: On the possibility of learning in reactive environments with arbitrary dependence. Theor. Comput. Sci. 405(3): 274-284 (2008)
	2007
108		Marcus Hutter, Rocco A. Servedio, Eiji Takimoto: Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings Springer 2007
107		Marcus Hutter, Rocco A. Servedio, Eiji Takimoto: Editors' Introduction. ALT 2007: 1-8
106		Marcus Hutter: The Loss Rank Principle for Model Selection. COLT 2007: 589-603
105		Marcus Hutter, Shane Legg: Temporal Difference Updating without a Learning Rate. NIPS 2007
104		Shane Legg, Marcus Hutter: A Collection of Definitions of Intelligence CoRR abs/0706.3639: (2007)
103		Marcus Hutter, Andrej Muchnik: On Semimeasures Predicting Martin-Loef Random Sequences CoRR abs/0708.2319: (2007)
102		Marcus Hutter: On Universal Prediction and Bayesian Confirmation CoRR abs/0709.1516: (2007)
101		Shane Legg, Marcus Hutter: Universal Intelligence: A Definition of Machine Intelligence CoRR abs/0712.3329: (2007)
100		Shane Legg, Marcus Hutter: Tests of Machine Intelligence CoRR abs/0712.3825: (2007)
99		Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Algorithmic Complexity Bounds on Future Prediction Errors CoRR abs/cs/0701120: (2007)
98		Marcus Hutter: Universal Algorithmic Intelligence: A mathematical top->down approach CoRR abs/cs/0701125: (2007)
97		Marcus Hutter: Algorithmic Information Theory: a brief non-technical guide to the field CoRR abs/cs/0703024: (2007)
96		Marcus Hutter: The Loss Rank Principle for Model Selection CoRR abs/math/0702804: (2007)
95		Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Algorithmic complexity bounds on future prediction errors. Inf. Comput. 205(2): 242-261 (2007)
94		Shane Legg, Marcus Hutter: Universal Intelligence: A Definition of Machine Intelligence. Minds and Machines 17(4): 391-444 (2007)
93		Marcus Hutter: Algorithmic information theory. Scholarpedia 2(3): 2519 (2007)
92		Marcus Hutter, Shane Legg, Paul M. B. Vitányi: Algorithmic probability. Scholarpedia 2(8): 2572 (2007)
91		Marcus Hutter, Andrej Muchnik: On semimeasures predicting Martin-Löf random sequences. Theor. Comput. Sci. 382(3): 247-261 (2007)
90		Marcus Hutter: On universal prediction and Bayesian confirmation. Theor. Comput. Sci. 384(1): 33-48 (2007)
	2006
89		Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi: Kolmogorov Complexity and Applications, 29.01. - 03.02.2006 Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2006
88		Shane Legg, Marcus Hutter: Tests of Machine Intelligence. 50 Years of Artificial Intelligence 2006: 232-242
87		Marcus Hutter: General Discounting Versus Average Reward. ALT 2006: 244-258
86		Daniil Ryabko, Marcus Hutter: Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence. ALT 2006: 334-347
85		Daniil Ryabko, Marcus Hutter: Sequence prediction for non-stationary processes. Combinatorial and Algorithmic Foundations of Pattern and Association Discovery 2006
84		Viktor Zhumatiy, Faustino J. Gomez, Marcus Hutter, Jürgen Schmidhuber: Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot. IAS 2006: 272-281
83		Marcus Hutter, Wolfgang Merkle, Paul M. B. Vitányi: 06051 Abstracts Collection -- Kolmogorov Complexity and Applications. Kolmogorov Complexity and Applications 2006
82		Alexey V. Chernov, Marcus Hutter, Jürgen Schmidhuber: Complexity Monotone in Conditions and Future Prediction Errors. Kolmogorov Complexity and Applications 2006
81		Daniil Ryabko, Marcus Hutter: Learning in Reactive Environments with Arbitrary Dependence. Kolmogorov Complexity and Applications 2006
80		Marcus Hutter: On the Foundations of Universal Sequence Prediction. TAMC 2006: 408-420
79		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)
78		Daniil Ryabko, Marcus Hutter: Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence CoRR abs/cs/0603110: (2006)
77		Marcus Hutter: On the Foundations of Universal Sequence Prediction CoRR abs/cs/0605009: (2006)
76		Shane Legg, Marcus Hutter: A Formal Measure of Machine Intelligence CoRR abs/cs/0605024: (2006)
75		Marcus Hutter: General Discounting versus Average Reward CoRR abs/cs/0605040: (2006)
74		Daniil Ryabko, Marcus Hutter: On Sequence Prediction for Arbitrary Measures CoRR abs/cs/0606077: (2006)
73		Marcus Hutter, Shane Legg: Fitness Uniform Optimization CoRR abs/cs/0610126: (2006)
72		Jan Poland, Marcus Hutter: MDL Convergence Speed for Bernoulli Sequences CoRR abs/math/0602505: (2006)
71		Marcus Hutter: Bayesian Regression of Piecewise Constant Functions CoRR abs/math/0606315: (2006)
70		Monaldo Mastrolilli, Marcus Hutter: Hybrid rounding techniques for knapsack problems. Discrete Applied Mathematics 154(4): 640-649 (2006)
69		Marcus Hutter, Shane Legg: Fitness uniform optimization. IEEE Trans. Evolutionary Computation 10(5): 568-589 (2006)
68		Marcus Hutter: Sequential predictions based on algorithmic complexity. J. Comput. Syst. Sci. 72(1): 95-117 (2006)
67		Jan Poland, Marcus Hutter: MDL convergence speed for Bernoulli sequences. Statistics and Computing 16(2): 161-175 (2006)
66		Marcus Hutter: On generalized computable universal priors and their convergence. Theor. Comput. Sci. 364(1): 27-41 (2006)
	2005
65		Jan Poland, Marcus Hutter: Defensive Universal Learning with Experts. ALT 2005: 356-370
64		Alexey V. Chernov, Marcus Hutter: Monotone Conditional Complexity Bounds on Future Prediction Errors. ALT 2005: 414-428
63		Shane Legg, Marcus Hutter: Fitness uniform deletion: a simple way to preserve diversity. GECCO 2005: 1271-1278
62		Shane Legg, Marcus Hutter: A Universal Measure of Intelligence for Artificial Agents. IJCAI 2005: 1509-1510
61		Marco Zaffalon, Marcus Hutter: Robust inference of trees. Ann. Math. Artif. Intell. 45(1-2): 215-239 (2005)
60		Jan Poland, Marcus Hutter: Master Algorithms for Active Experts Problems based on Increasing Loss Values CoRR abs/cs/0502067: (2005)
59		Marcus Hutter: On Generalized Computable Universal Priors and their Convergence CoRR abs/cs/0503026: (2005)
58		Shane Legg, Marcus Hutter: Fitness Uniform Deletion: A Simple Way to Preserve Diversity CoRR abs/cs/0504035: (2005)
57		Marcus Hutter, Jan Poland: Adaptive Online Prediction by Following the Perturbed Leader CoRR abs/cs/0504078: (2005)
56		Jan Poland, Marcus Hutter: Asymptotics of Discrete MDL for Online Prediction CoRR abs/cs/0506022: (2005)
55		Alexey V. Chernov, Marcus Hutter: Monotone Conditional Complexity Bounds on Future Prediction Errors CoRR abs/cs/0507041: (2005)
54		Jan Poland, Marcus Hutter: Defensive Universal Learning with Experts CoRR abs/cs/0507044: (2005)
53		Marcus Hutter: Sequential Predictions based on Algorithmic Complexity CoRR abs/cs/0508043: (2005)
52		Jan Poland, Marcus Hutter: Universal Learning of Repeated Matrix Games CoRR abs/cs/0508073: (2005)
51		Marco Zaffalon, Marcus Hutter: Robust Inference of Trees CoRR abs/cs/0511087: (2005)
50		Jan Poland, Marcus Hutter: Strong Asymptotic Assertions for Discrete MDL in Regression and Classification CoRR abs/math/0502315: (2005)
49		Marcus Hutter, Marco Zaffalon: Distribution of mutual information from complete and incomplete data. Computational Statistics & Data Analysis 48(3): 633-657 (2005)
48		Jan Poland, Marcus Hutter: Asymptotics of discrete MDL for online prediction. IEEE Transactions on Information Theory 51(11): 3780-3795 (2005)
47		Marcus Hutter, Jan Poland: Adaptive Online Prediction by Following the Perturbed Leader. Journal of Machine Learning Research 6: 639-660 (2005)
	2004
46		Marcus Hutter, Andrej Muchnik: Universal Convergence of Semimeasures on Individual Random Sequences. ALT 2004: 234-248
45		Marcus Hutter, Jan Poland: Prediction with Expert Advice by Following the Perturbed Leader for General Weights. ALT 2004: 279-293
44		Jan Poland, Marcus Hutter: On the Convergence Speed of MDL Predictions for Bernoulli Sequences. ALT 2004: 294-308
43		Jan Poland, Marcus Hutter: Convergence of Discrete MDL for Sequential Prediction. COLT 2004: 300-314
42		Marcus Hutter, Marco Zaffalon: Distribution of Mutual Information from Complete and Incomplete Data CoRR cs.LG/0403025: (2004)
41		Shane Legg, Marcus Hutter, Akshat Kumar: Tournament versus Fitness Uniform Selection CoRR cs.LG/0403038: (2004)
40		Jan Poland, Marcus Hutter: Convergence of Discrete MDL for Sequential Prediction CoRR cs.LG/0404057: (2004)
39		Marcus Hutter, Jan Poland: Prediction with Expert Advice by Following the Perturbed Leader for General Weights CoRR cs.LG/0405043: (2004)
38		Jan Poland, Marcus Hutter: On the Convergence Speed of MDL Predictions for Bernoulli Sequences CoRR cs.LG/0407039: (2004)
37		Marcus Hutter, Andrej Muchnik: Universal Convergence of Semimeasures on Individual Random Sequences CoRR cs.LG/0407057: (2004)
	2003
36		Marcus Hutter: On the Existence and Convergence of Computable Universal Priors. ALT 2003: 298-312
35		Marcus Hutter: Sequence Prediction Based on Monotone Complexity. COLT 2003: 506-521
34		Marcus Hutter: An Open Problem Regarding the Convergence of Universal A Priori Probability. COLT 2003: 738-740
33		Marcus Hutter: Robust Estimators under the Imprecise Dirichlet Model. ISIPTA 2003: 274-289
32		Marcus Hutter, Marco Zaffalon: Bayesian Treatment of Incomplete Discrete Data Applied to Mutual Information and Feature Selection. KI 2003: 396-406
31		Marcus Hutter: Sequence Prediction based on Monotone Complexity CoRR cs.AI/0306036: (2003)
30		Marcus Hutter: Optimal Sequential Decisions based on Algorithmic Probability CoRR cs.AI/0306091: (2003)
29		Monaldo Mastrolilli, Marcus Hutter: Hybrid Rounding Techniques for Knapsack Problems CoRR cs.CC/0305002: (2003)
28		Marcus Hutter: Convergence and Loss Bounds for Bayesian Sequence Prediction CoRR cs.LG/0301014: (2003)
27		Marcus Hutter: On the Existence and Convergence Computable Universal Priors CoRR cs.LG/0305052: (2003)
26		Marcus Hutter, Marco Zaffalon: Bayesian Treatment of Incomplete Discrete Data applied to Mutual Information and Feature Selection CoRR cs.LG/0306126: (2003)
25		Marcus Hutter: Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet CoRR cs.LG/0311014: (2003)
24		Marcus Hutter: Convergence and loss bounds for Bayesian sequence prediction. IEEE Transactions on Information Theory 49(8): 2061-2067 (2003)
23		Marcus Hutter: Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet. Journal of Machine Learning Research 4: 971-1000 (2003)
	2002
22		Marcus Hutter: Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures. COLT 2002: 364-379
21		Marco Zaffalon, Marcus Hutter: Robust Feature Selection by Mutual Information Distributions. UAI 2002: 577-584
20		Marcus Hutter: Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures CoRR cs.AI/0204040: (2002)
19		Marco Zaffalon, Marcus Hutter: Robust Feature Selection by Mutual Information Distributions CoRR cs.AI/0206006: (2002)
18		Marcus Hutter: The Fastest and Shortest Algorithm for All Well-Defined Problems CoRR cs.CC/0206022: (2002)
17		Marcus Hutter: The Fastest and Shortest Algorithm for all Well-Defined Problems. Int. J. Found. Comput. Sci. 13(3): 431-443 (2002)
	2001
16		Marcus Hutter: Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions. ECML 2001: 226-238
15		Marcus Hutter: Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences. ECML 2001: 239-250
14		Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Market-Based Reinforcement Learning in Partially Observable Worlds. ICANN 2001: 865-873
13		Marcus Hutter: General Loss Bounds for Universal Sequence Prediction. ICML 2001: 210-217
12		Marcus Hutter: Distribution of Mutual Information. NIPS 2001: 399-406
11		Marcus Hutter: General Loss Bounds for Universal Sequence Prediction CoRR cs.AI/0101019: (2001)
10		Marcus Hutter: Fitness Uniform Selection to Preserve Genetic Diversity CoRR cs.AI/0103015: (2001)
9		Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Market-Based Reinforcement Learning in Partially Observable Worlds CoRR cs.AI/0105025: (2001)
8		Ivo Kwee, Marcus Hutter, Jürgen Schmidhuber: Gradient-based Reinforcement Planning in Policy-Search Methods CoRR cs.AI/0111060: (2001)
7		Marcus Hutter: Distribution of Mutual Information CoRR cs.AI/0112019: (2001)
6		Marcus Hutter: An effective Procedure for Speeding up Algorithms CoRR cs.CC/0102018: (2001)
5		Marcus Hutter: Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences CoRR cs.LG/0106036: (2001)
4		Marcus Hutter: New Error Bounds for Solomonoff Prediction. J. Comput. Syst. Sci. 62(4): 653-667 (2001)
	2000
3		Marcus Hutter: A Theory of Universal Artificial Intelligence based on Algorithmic Complexity CoRR cs.AI/0004001: (2000)
2		Marcus Hutter: Towards a Universal Theory of Artificial Intelligence based on Algorithmic Probability and Sequential Decision Theory CoRR cs.AI/0012011: (2000)
	1999
1		Marcus Hutter: New Error Bounds for Solomonoff Prediction CoRR cs.AI/9912008: (1999)

Coauthor Index

1	Francesco Bertoni	[129] [133] [140]
2	Michael H. Bowling	[152] [173]
3	Nathan Brewer	[123] [135] [163]
4	Wray L. Buntine (Wray Lindsay Buntine)	[138]
5	Alexey V. Chernov	[55] [64] [82] [95] [99]
6	Vaibhav Gavane	[155] [167]
7	Ben Goertzel	[142]
8	Faustino J. Gomez	[79] [84]
9	Kassel Hingee	[116] [118]
10	Srimal Jayawardena	[135] [162] [163] [171]
11	Huidong Jin	[128] [131]
12	Akshat Kumar	[41]
13	Ivo Kwee	[8] [9] [14] [129] [133] [140]
14	Tor Lattimore	[151] [154] [155] [156] [164] [165] [167] [170]
15	Shane Legg	[41] [58] [62] [63] [69] [73] [76] [88] [92] [94] [100] [101] [104] [105] [114]
16	Monaldo Mastrolilli	[29] [70]
17	Wolfgang Merkle	[83] [89]
18	Andrej Muchnik (Andrei A. Muchnik)	[37] [46] [91] [103]
19	Kee Siong Ng	[124] [137] [146] [148] [152] [173]
20	Phuong Nguyen	[153] [161]
21	Alexander O'Neill	[172] [174]
22	Alberto Piatti	[120] [127]
23	Jan Poland	[38] [39] [40] [43] [44] [45] [47] [48] [50] [52] [54] [56] [57] [60] [65] [67] [72]
24	Paola M. V. Rancoita	[129] [133] [140]
25	Samuel Rathmanner	[158]
26	Daniil Ryabko	[74] [78] [81] [85] [86] [109] [113] [117]
27	Scott Sanner	[175]
28	Jürgen Schmidhuber	[8] [9] [14] [79] [82] [84] [95] [99]
29	Rocco A. Servedio	[107] [108] [119]
30	Wen Shao	[172] [174]
31	David Silver	[124] [137] [146] [148]
32	Frank Stephan	[145] [147]
33	Peter Sunehag	[136] [144] [149] [150] [153] [157] [161] [166] [172] [174]
34	Eiji Takimoto	[107] [108]
35	Minh-Ngoc Tran	[134] [139]
36	Fabio Trojani	[120] [127]
37	William T. B. Uther	[148]
38	Joel Veness	[124] [137] [146] [148] [152] [173]
39	Paul M. B. Vitányi	[83] [89] [92]
40	Vladimir Vovk (Volodya Vovk, V. G. Vovk)	[145] [147]
41	Ian Wood	[150]
42	Di Yang	[162] [171]
43	Marco Zaffalon	[19] [21] [26] [32] [42] [49] [51] [61] [120] [127]
44	Thomas Zeugmann	[145] [147]
45	Ke Zhang	[128] [131]
46	Viktor Zhumatiy	[79] [84]

Colors in the list of coauthors

Last update Thu May 31 18:55:10 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page