Marcus Hutter

Francesco Bertoni

Ivo Kwee

Proceedings of the Distributed Computing, 2009

2008

On the possibility of learning in reactive environments with arbitrary dependence.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2008

Algorithmic complexity.

[BibT_eX]

[DOI]

Scholarpedia, 2008

Feature Dynamic Bayesian Networks

[BibT_eX]

[DOI]

CoRR, 2008

Feature Markov Decision Processes

[BibT_eX]

[DOI]

CoRR, 2008

Predictive Hypothesis Identification

[BibT_eX]

[DOI]

CoRR, 2008

Predicting non-stationary processes.

[BibT_eX]

[DOI]

Appl. Math. Lett., 2008

Equivalence of probabilistic tournament and polynomial ranking selection.

[BibT_eX]

[DOI]

Kassel Hingee

Proceedings of the IEEE Congress on Evolutionary Computation, 2008

2007

Universal Algorithmic Intelligence: A Mathematical Top→Down Approach.

[BibT_eX]

[DOI]

Proceedings of the Artificial General Intelligence, 2007

On semimeasures predicting Martin-Löf random sequences.

[BibT_eX]

[DOI]

Andrej Muchnik

Theor. Comput. Sci., 2007

On universal prediction and Bayesian confirmation.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2007

Algorithmic probability.

[BibT_eX]

[DOI]

Paul M. B. Vitányi

Scholarpedia, 2007

Algorithmic information theory.

[BibT_eX]

[DOI]

Scholarpedia, 2007

Universal Intelligence: A Definition of Machine Intelligence.

[BibT_eX]

[DOI]

Minds Mach., 2007

Algorithmic complexity bounds on future prediction errors.

[BibT_eX]

[DOI]

Alexey V. Chernov

Inf. Comput., 2007

Algorithmic Information Theory: a brief non-technical guide to the field

[BibT_eX]

[DOI]

CoRR, 2007

Universal Algorithmic Intelligence: A mathematical top->down approach

[BibT_eX]

[DOI]

CoRR, 2007

On Semimeasures Predicting Martin-Loef Random Sequences

[BibT_eX]

[DOI]

Andrej Muchnik

CoRR, 2007

Temporal Difference Updating without a Learning Rate.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

On Sequence Prediction for Arbitrary Measures.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Information Theory, 2007

The Loss Rank Principle for Model Selection.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 20th Annual Conference on Learning Theory, 2007

Editors' Introduction.

[BibT_eX]

[DOI]

Rocco A. Servedio

Eiji Takimoto

Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

2006

Fitness uniform optimization.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 2006

On generalized computable universal priors and their convergence.

[BibT_eX]

[DOI]

Theor. Comput. Sci., 2006

MDL convergence speed for Bernoulli sequences.

[BibT_eX]

[DOI]

Stat. Comput., 2006

Sequential predictions based on algorithmic complexity.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 2006

Hybrid rounding techniques for knapsack problems.

[BibT_eX]

[DOI]

Monaldo Mastrolilli

Discret. Appl. Math., 2006

Bayesian Regression of Piecewise Constant Functions

[BibT_eX]

[DOI]

CoRR, 2006

A Formal Measure of Machine Intelligence

[BibT_eX]

[DOI]

CoRR, 2006

On the Foundations of Universal Sequence Prediction.

[BibT_eX]

[DOI]

Proceedings of the Theory and Applications of Models of Computation, 2006

Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot.

[BibT_eX]

Proceedings of the Intelligent Autonomous Systems 9, 2006

Learning in Reactive Environments with Arbitrary Dependence.

[BibT_eX]

[DOI]

Proceedings of the Kolmogorov Complexity and Applications, 29.01. - 03.02.2006, 2006

Sequence prediction for non-stationary processes.

[BibT_eX]

[DOI]

Proceedings of the Combinatorial and Algorithmic Foundations of Pattern and Association Discovery, 14.05., 2006

06051 Abstracts Collection -- Kolmogorov Complexity and Applications.

[BibT_eX]

[DOI]

Wolfgang Merkle

Paul M. B. Vitányi

Proceedings of the Kolmogorov Complexity and Applications, 29.01. - 03.02.2006, 2006

Complexity Monotone in Conditions and Future Prediction Errors.

[BibT_eX]

[DOI]

Alexey V. Chernov

Proceedings of the Kolmogorov Complexity and Applications, 29.01. - 03.02.2006, 2006

Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

General Discounting Versus Average Reward.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

Tests of Machine Intelligence.

[BibT_eX]

[DOI]

Proceedings of the 50 Years of Artificial Intelligence, 2006

A Collection of Definitions of Intelligence.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms, 2006

2005

Universal Artificial Intellegence - Sequential Decisions Based on Algorithmic Probability

[BibT_eX]

[DOI]

Texts in Theoretical Computer Science. An EATCS Series, Springer, ISBN: 978-3-540-26877-2, 2005

Asymptotics of discrete MDL for online prediction.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2005

Adaptive Online Prediction by Following the Perturbed Leader.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2005

Distribution of mutual information from complete and incomplete data.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2005

Strong Asymptotic Assertions for Discrete MDL in Regression and Classification

[BibT_eX]

[DOI]

CoRR, 2005

Universal Learning of Repeated Matrix Games

[BibT_eX]

[DOI]

CoRR, 2005

Master Algorithms for Active Experts Problems based on Increasing Loss Values

[BibT_eX]

[DOI]

CoRR, 2005

Robust inference of trees.

[BibT_eX]

[DOI]

Ann. Math. Artif. Intell., 2005

A Universal Measure of Intelligence for Artificial Agents.

[BibT_eX]

[DOI]

Proceedings of the IJCAI-05, 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.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2005

Defensive Universal Learning with Experts.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

Monotone Conditional Complexity Bounds on Future Prediction Errors.

[BibT_eX]

[DOI]

Alexey V. Chernov

Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

Fast Non-Parametric Bayesian Inference on Infinite Trees.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Convergence of Discrete MDL for Sequential Prediction.

[BibT_eX]

[DOI]

Proceedings of the Learning Theory, 17th Annual Conference on Learning Theory, 2004

Tournament versus fitness uniform selection.

[BibT_eX]

[DOI]

Akshat Kumar

Proceedings of the IEEE Congress on Evolutionary Computation, 2004

On the Convergence Speed of MDL Predictions for Bernoulli Sequences.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

Prediction with Expert Advice by Following the Perturbed Leader for General Weights.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

Universal Convergence of Semimeasures on Individual Random Sequences.

[BibT_eX]

[DOI]

Andrej Muchnik

Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003

Convergence and loss bounds for Bayesian sequence prediction.

[BibT_eX]

[DOI]

IEEE Trans. Inf. Theory, 2003

Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2003

Optimal Sequential Decisions based on Algorithmic Probability

[BibT_eX]

[DOI]

CoRR, 2003

Bayesian Treatment of Incomplete Discrete Data Applied to Mutual Information and Feature Selection.

[BibT_eX]

[DOI]

Proceedings of the KI 2003: Advances in Artificial Intelligence, 2003

Robust Estimators under the Imprecise Dirichlet Model.

[BibT_eX]

[DOI]

Proceedings of the ISIPTA '03, 2003

An Open Problem Regarding the Convergence of Universal A Priori Probability.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

Sequence Prediction Based on Monotone Complexity.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory and Kernel Machines, 2003

On the Existence and Convergence of Computable Universal Priors.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 14th International Conference, 2003

2002

The Fastest and Shortest Algorithm for all Well-Defined Problems.

[BibT_eX]

[DOI]

Int. J. Found. Comput. Sci., 2002

Robust Feature Selection by Mutual Information Distributions.

[BibT_eX]

[DOI]

Proceedings of the UAI '02, 2002

Self-Optimizing and Pareto-Optimal Policies in General Environments Based on Bayes-Mixtures.

[BibT_eX]

[DOI]

Proceedings of the Computational Learning Theory, 2002

Fitness uniform selection to preserve genetic diversity.

[BibT_eX]

[DOI]

Proceedings of the 2002 Congress on Evolutionary Computation, 2002

2001

New Error Bounds for Solomonoff Prediction.

[BibT_eX]

[DOI]

J. Comput. Syst. Sci., 2001

An effective Procedure for Speeding up Algorithms

[BibT_eX]

[DOI]

CoRR, 2001

Gradient-based Reinforcement Planning in Policy-Search Methods

[BibT_eX]

[DOI]

Ivo Kwee

CoRR, 2001

Distribution of Mutual Information.

[BibT_eX]

[DOI]

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.

[BibT_eX]

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

Market-Based Reinforcement Learning in Partially Observable Worlds.

[BibT_eX]

[DOI]

Ivo Kwee

Proceedings of the Artificial Neural Networks, 2001

Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: EMCL 2001, 2001

Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: EMCL 2001, 2001

2000

Towards a Universal Theory of Artificial Intelligence based on Algorithmic Probability and Sequential Decision Theory

[BibT_eX]

[DOI]

CoRR, 2000

A Theory of Universal Artificial Intelligence based on Algorithmic Complexity

[BibT_eX]

[DOI]