Marcus Hutter

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Marcus Hutter is affiliated with the following schools: Ludwig Maximilian University of Munich, Technical University of Munich, Australian National University

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Marcus Hutter

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#303

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Marcus Hutter's Degrees

PhD Computer Science Australian National University

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Why Is Marcus Hutter Influential?

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According to Wikipedia, Marcus Hutter is a professor and artificial intelligence researcher. A Senior Scientist at DeepMind, he is researching the mathematical foundations of artificial general intelligence. He is on leave from his professorship at the ANU College of Engineering and Computer Science of the Australian National University in Canberra, Australia. Hutter studied physics and computer science at the Technical University of Munich. In 2000 he joined Jürgen Schmidhuber's group at the Istituto Dalle Molle di Studi sull'Intelligenza Artificiale in Manno, Switzerland. He developed a mathematical theory of artificial general intelligence. His book Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability was published by Springer in 2005.

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Marcus Hutter's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Algorithmic information theory (2007) (552)
Universal Intelligence: A Definition of Machine Intelligence (2007) (538)
Universal Artificial Intellegence - Sequential Decisions Based on Algorithmic Probability (2005) (460)
A Collection of Definitions of Intelligence (2007) (412)
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data (2009) (349)
Model Growth (2002) (249)
A Monte-Carlo AIXI Approximation (2009) (175)
PAC Bounds for Discounted MDPs (2012) (173)
Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability (Texts in Theoretical Computer Science. An EATCS Series) (2006) (141)
Distribution of Mutual Information (2001) (126)
Adaptive Online Prediction by Following the Perturbed Leader (2005) (126)
Robust Feature Selection by Mutual Information Distributions (2002) (123)
Discriminative Hierarchical Rank Pooling for Activity Recognition (2016) (113)
Count-Based Exploration in Feature Space for Reinforcement Learning (2017) (102)
On Universal Prediction and Bayesian Confirmation (2007) (99)
A Philosophical Treatise of Universal Induction (2011) (97)
Universal Algorithmic Intelligence: A Mathematical Top→Down Approach (2007) (95)
Fitness uniform selection to preserve genetic diversity (2001) (84)
AGI Safety Literature Review (2018) (79)
Fitness uniform optimization (2006) (76)
A Formal Measure of Machine Intelligence (2006) (76)
The Fastest and Shortest Algorithm for all Well-Defined Problems (2000) (76)
A Theory of Universal Artificial Intelligence based on Algorithmic Complexity (2000) (73)
A Bayesian Review of the Poisson-Dirichlet Process (2010) (69)
Distribution of mutual information from complete and incomplete data (2004) (66)
Feature Reinforcement Learning: Part I. Unstructured MDPs (2009) (65)
Bayesian DNA copy number analysis (2009) (63)
Logarithmic Pruning is All You Need (2020) (61)
The Sample-Complexity of General Reinforcement Learning (2013) (54)
Self-Optimizing and Pareto-Optimal Policies in General Environments based on Bayes-Mixtures (2002) (53)
Towards a Universal Theory of Artificial Intelligence Based on Algorithmic Probability and Sequential Decisions (2000) (52)
Near-optimal PAC bounds for discounted MDPs (2014) (51)
On Thompson Sampling and Asymptotic Optimality (2017) (50)
Context Tree Switching (2011) (47)
Asymptotics of discrete MDL for online prediction (2005) (43)
Reward tampering problems and solutions in reinforcement learning: a causal influence diagram perspective (2019) (43)
One Decade of Universal Artificial Intelligence (2012) (43)
Universal Knowledge-Seeking Agents for Stochastic Environments (2013) (42)
No Free Lunch versus Occam's Razor in Supervised Learning (2011) (42)
New Error Bounds for Solomonoff Prediction (1999) (38)
General time consistent discounting (2014) (36)
Bad Universal Priors and Notions of Optimality (2015) (36)
Convergence and Loss Bounds for Bayesian Sequence Prediction (2003) (36)
Thompson Sampling is Asymptotically Optimal in General Environments (2016) (36)
Optimality of universal Bayesian prediction for general loss and alphabet (2003) (35)
Exact Bayesian regression of piecewise constant functions (2007) (34)
Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet (2003) (34)
Prediction with Expert Advice by Following the Perturbed Leader for General Weights (2004) (33)
Asymptotically Optimal Agents (2011) (33)
A Universal Measure of Intelligence for Artificial Agents (2005) (32)
Avoiding Wireheading with Value Reinforcement Learning (2016) (32)
Open Problems in Universal Induction & Intelligence (2009) (31)
Tournament versus fitness uniform selection (2004) (31)
Reinforcement Learning via AIXI Approximation (2010) (28)
A Complete Theory of Everything (Will Be Subjective) (2009) (28)
Can Intelligence Explode? (2012) (28)
Algorithmic complexity (2008) (28)
Market-Based Reinforcement Learning in Partially Observable Worlds (2001) (26)
Shaking the foundations: delusions in sequence models for interaction and control (2021) (26)
Gated Linear Networks (2019) (26)
Probabilities on Sentences in an Expressive Logic (2012) (26)
Matching 2-D ellipses to 3-D circles with application to vehicle pose identification (2009) (26)
Compress and Control (2014) (26)
On the Role of Neural Collapse in Transfer Learning (2021) (26)
Self-Modification of Policy and Utility Function in Rational Agents (2016) (25)
Defensive Universal Learning with Experts (2005) (24)
Limits of Learning about a Categorical Latent Variable under Prior Near-Ignorance (2007) (24)
Tests of Machine Intelligence (2007) (24)
Extreme State Aggregation beyond MDPs (2014) (23)
On the Possibility of Learning in Reactive Environments with Arbitrary Dependence (2008) (23)
Convergence and Error Bounds for Universal Prediction of Nonbinary Sequences (2001) (23)
Learning Curve Theory (2021) (22)
Counterfactual Credit Assignment in Model-Free Reinforcement Learning (2020) (21)
Hybrid rounding techniques for knapsack problems (2003) (21)
Feature Dynamic Bayesian Networks (2008) (21)
A rapid and efficient learning rule for biological neural circuits (2021) (21)
Algorithmic probability (2007) (20)
Temporal Difference Updating without a Learning Rate (2007) (20)
Sequence Prediction Based on Monotone Complexity (2003) (19)
Convergence of Discrete MDL for Sequential Prediction (2004) (19)
On the Foundations of Universal Sequence Prediction (2006) (19)
On the Convergence Speed of MDL Predictions for Bernoulli Sequences (2004) (19)
Rationality, optimism and guarantees in general reinforcement learning (2015) (18)
Death and Suicide in Universal Artificial Intelligence (2016) (18)
Predicting non-stationary processes (2008) (18)
General Loss Bounds for Universal Sequence Prediction (2001) (18)
Equivalence of probabilistic tournament and polynomial ranking selection (2008) (18)
On semimeasures predicting Martin-Löf random sequences (2007) (17)
Robust Estimators under the Imprecise Dirichlet Model (2003) (17)
An integrated Bayesian analysis of LOH and copy number data (2010) (17)
Universal Learning of Repeated Matrix Games (2005) (17)
Consistency of Feature Markov Processes (2010) (17)
On the Existence and Convergence of Computable Universal Priors (2003) (17)
MDL convergence speed for Bernoulli sequences (2006) (17)
A Gentle Introduction to The Universal Algorithmic Agent AIXI (2003) (17)
Universal Reinforcement Learning Algorithms: Survey and Experiments (2017) (17)
Discrete MDL Predicts in Total Variation (2009) (16)
Time Consistent Discounting (2011) (16)
On Q-learning Convergence for Non-Markov Decision Processes (2018) (16)
Feature Reinforcement Learning in Practice (2011) (16)
Extreme state aggregation beyond Markov decision processes (2016) (15)
Asymptotically Unambitious Artificial General Intelligence (2019) (15)
Sparse Adaptive Dirichlet-Multinomial-like Processes (2013) (15)
Feature Reinforcement Learning: State of the Art (2014) (15)
Q-learning for history-based reinforcement learning (2013) (15)
Universal Convergence of Semimeasures on Individual Random Sequences (2004) (15)
Optimistic Agents Are Asymptotically Optimal (2012) (14)
Sequential Extensions of Causal and Evidential Decision Theory (2015) (14)
Instantons in QCD: Theory and Application of the Instanton Liquid Model (1996) (14)
General Discounting Versus Average Reward (2006) (14)
On Representing (Anti)Symmetric Functions (2020) (14)
Feature Markov Decision Processes (2008) (14)
On Sequence Prediction for Arbitrary Measures (2006) (14)
Fitness uniform deletion: a simple way to preserve diversity (2005) (13)
Algorithmic Information Theory: a brief non-technical guide to the field (2007) (13)
Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search (2015) (13)
Free Lunch for optimisation under the universal distribution (2014) (13)
Sequential Predictions based on Algorithmic Complexity (2005) (12)
Can we measure the difficulty of an optimization problem? (2014) (12)
Context Tree Maximizing (2021) (12)
Sequential Decisions based on Algorithmic Probability (2008) (12)
On the Computability of Solomonoff Induction and Knowledge-Seeking (2015) (12)
Formal Algorithms for Transformers (2022) (12)
Fast Non-Parametric Bayesian Inference on Infinite Trees (2004) (12)
Gradient-based Reinforcement Planning in Policy-Search Methods (2001) (11)
Adaptive Context Tree Weighting (2012) (11)
Proceedings of the Second Conference on Artificial General Intelligence (2009) (11)
Algorithmic complexity bounds on future prediction errors (2007) (11)
Robust inference of trees (2005) (11)
Axioms for Rational Reinforcement Learning (2011) (11)
The subjective computable universe (2012) (11)
The Alignment Problem for Bayesian History-Based Reinforcement Learners∗ (2019) (11)
Context tree maximizing reinforcement learning (2012) (10)
On the Computability of AIXI (2015) (10)
Strong Asymptotic Assertions for Discrete MDL in Regression and Classification (2005) (9)
Universal Prediction of Selected Bits (2011) (9)
A Game-Theoretic Analysis of the Off-Switch Game (2017) (9)
Neural Networks and the Chomsky Hierarchy (2022) (9)
Intelligence as Inference or Forcing Occam on the World (2014) (9)
Optimistic AIXI (2012) (9)
Sequence prediction for non-stationary processes (2006) (9)
Bayesian Regression of Piecewise Constant Functions (2006) (9)
Online Learning in Contextual Bandits using Gated Linear Networks (2020) (8)
A Strongly Asymptotically Optimal Agent in General Environments (2019) (8)
Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search (2015) (8)
Metric State Space Reinforcement Learning for a Vision-Capable Mobile Robot (2006) (8)
Universal Learning Theory (2011) (8)
Feature Reinforcement Learning using Looping Suffix Trees (2012) (8)
Multi-task reinforcement learning : shaping and feature selection (2011) (8)
A Novel Illumination-Invariant Loss for Monocular 3D Pose Estimation (2011) (8)
Pessimism About Unknown Unknowns Inspires Conservatism (2020) (8)
Loss Bounds and Time Complexity for Speed Priors (2016) (7)
On Ensemble Techniques for AIXI Approximation (2012) (7)
Family structure from periodic solutions of an improved gap equation (1996) (7)
On the computability of Solomonoff induction and AIXI (2017) (7)
Principles of Solomonoff Induction and AIXI (2011) (7)
3D Model Assisted Image Segmentation (2011) (7)
Performance Guarantees for Homomorphisms Beyond Markov Decision Processes (2018) (6)
An Open Problem Regarding the Convergence of Universal A Priori Probability (2003) (6)
A Combinatorial Perspective on Transfer Learning (2020) (6)
On Martin-Löf Convergence of Solomonoff's Mixture (2013) (6)
Reinforcement learning with value advice (2014) (6)
Universal sequential decisions in unknown environments (2003) (6)
Bayesian Reinforcement Learning with Exploration (2014) (6)
A Topological Approach to Meta-heuristics: Analytical Results on the BFS vs. DFS Algorithm Selection Problem (2015) (6)
The Loss Rank Principle for Model Selection (2007) (6)
Model selection with the Loss Rank Principle (2010) (6)
On Generalized Computable Universal Priors and their Convergence (2005) (6)
Ergodic MDPs Admit Self-Optimising Policies (2004) (5)
Advanced Artificial Agents Intervene in the Provision of Reward (2022) (5)
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence (2006) (5)
Sparse Sequential Dirichlet Coding (2012) (5)
Online Learning of k-CNF Boolean Functions (2014) (5)
Gauge Invariant Quark Propagator in the Instanton Background (1995) (5)
Monotone Conditional Complexity Bounds on Future Prediction Errors (2005) (5)
Universal Artificial Intelligence-Practical Agents and Fundamental Challenges (2016) (5)
Gluon Mass from Instantons (1995) (5)
Learning Agents with Evolving Hypothesis Classes (2013) (4)
Reward-Punishment Symmetric Universal Intelligence (2021) (4)
Generalised Discount Functions applied to a Monte-Carlo AI u Implementation (2017) (4)
Bayesian Treatment of Incomplete Discrete Data applied to Mutual Information and Feature Selection (2003) (4)
Isotuning With Applications To Scale-Free Online Learning (2021) (4)
Uniqueness and Complexity of Inverse MDP Models (2022) (4)
Indefinitely Oscillating Martingales (2014) (4)
Concentration and Confidence for Discrete Bayesian Sequence Predictors (2013) (4)
Distribution of mutual information for robust feature selection (2002) (4)
Coding of Non-Stationary Sources as a Foundation for Detecting Change Points and Outliers in Binary Time-Series (2012) (4)
Optimal Sequential Decisions based on Algorithmic Probability (2003) (4)
Solomonoff Induction Violates Nicod's Criterion (2015) (4)
Exact Reduction of Huge Action Spaces in General Reinforcement Learning (2020) (4)
A Taxonomy for Abstract Environments. (2004) (4)
Context Tree Weighting (2013) (4)
Practical robust estimators for the imprecise Dirichlet model (2009) (4)
A Gentle Introduction to Quantum Computing Algorithms with Applications to Universal Prediction (2020) (4)
Matching 2-D Ellipses to 3-D Circles with Application to Vehicle Pose Estimation (2009) (4)
Artificial general intelligence: Proceedings of the Third Conference on Artificial General Intelligence, AGI 2010, Lugano, Switzerland, March 5-8, 2010 (2010) (3)
A Dual Process Theory of Optimistic Cognition (2014) (3)
Unifying probability and logic for learning (2013) (3)
Observer localization in multiverse theories (2010) (3)
Kolmogorov Complexity and Applications (2006) (3)
Towards a Universal Theory of Artificial Intelligence (2002) (3)
Featureless 2D–3D pose estimation by minimising an illumination-invariant loss (2010) (3)
Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009 (2009) (3)
The mass of the η′ in self-dual QCD (1995) (2)
Master Algorithms for Active Experts Problems based on Increasing Loss Values (2005) (2)
A Causal Influence Diagram Perspective (2019) (2)
Atari-5: Distilling the Arcade Learning Environment down to Five Games (2022) (2)
Predictive Hypothesis Identification (2008) (2)
Algorithmic Learning Theory, 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, Proceedings (2007) (2)
Offline to Online Conversion (2014) (2)
Model Selection by Loss Rank for Classification and Unsupervised Learning (2010) (2)
Natural Halting Probabilities , Partial Randomness , and Zeta Functions (2006) (2)
On Martin-Löf (non-)convergence of Solomonoff's universal mixture (2015) (2)
Sequential Learning Of Neural Networks for Prequential MDL (2022) (2)
Recent Advances in Reinforcement Learning - 9th European Workshop, EWRL 2011. (2012) (2)
Intelligence and Unambitiousness Using Algorithmic Information Theory (2021) (2)
Instantons and meson correlation functions in QCD (1995) (2)
Testing Independence of Exchangeable Random Variables (2022) (1)
Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence (2011) (1)
A Noise Tolerant Watershed Transformation with Viscous Force for Seeded Image Segmentation (2012) (1)
Curiosity Killed the Cat and the Asymptotically Optimal Agent (2020) (1)
To create a super-intelligent machine, start with an equation (2013) (1)
Tractability of batch to sequential conversion (2018) (1)
Conditions on Features for Temporal Difference-Like Methods to Converge (2019) (1)
Dynamic Intrusion Detection Method for Mobile Ad Hoc Network Using CPDOD Algorithm (2017) (1)
Strong Asymptotic Optimality in General Environments (2019) (1)
Reflective Features Detection and Hierarchical Reflections Separation in Image Sequences (2014) (1)
Proton Spin in the Instanton Background (1995) (1)
Bayesian Joint Estimation of CN and LOH Aberrations (2009) (1)
Erratum to “Family structure from periodic solutions of an improved gap equation” [Nucl. Phys. B 484 (1997) 80–96] (1997) (1)
Classification by decomposition: a novel approach to classification of symmetric 2 · 2 games (2021) (1)
Proceedings of the 18th international conference on Algorithmic Learning Theory (2007) (1)
The Alignment Problem for History-Based Bayesian Reinforcement Learners ∗ PUBLIC DRAFT (2018) (1)
An effective Procedure for Speeding up Algorithms (2001) (1)
Convergence of Binarized Context-tree Weighting for Estimating Distributions of Stationary Sources (2018) (1)
Algorithmic Learning Theory, 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings (2010) (1)
Generalization Bounds for Transfer Learning with Pretrained Classifiers (2022) (1)
Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning (2015) (1)
How to Predict with Bayes, MDL, and Experts (2005) (1)
Memory-Based Meta-Learning on Non-Stationary Distributions (2023) (0)
Preface: Guest Editors' foreword (2013) (0)
Intelligence : Many definitions (2006) (0)
U-Clip: On-Average Unbiased Stochastic Gradient Clipping (2023) (0)
Foundations of Induction (2011) (0)
The Universal Algorithmic Agent AIXI (2005) (0)
Reinforcement Learning (Dagstuhl Seminar 13321) (2013) (0)
of Random Sequences (2007) (0)
Feature Reinforcement Learning: Part II. Structured MDPs (2021) (0)
Recent Advances in Reinforcement Learning (2011) (0)
Editors' Introduction (2007) (0)
Proc. 3rd Conference on Artificial General Intelligence (2010) (0)
Fairness without Regret (2019) (0)
Foundations of Machine Learning (2008) (0)
Learning in Reactive Environments with Arbitrary Dependence (2006) (0)
Asymptotics of Discrete MDL for Online Prediction. main (2020) (0)
06051 Abstracts Collection -- Kolmogorov Complexity and Applications (2006) (0)
Report from Dagstuhl Seminar 13321 Reinforcement Learning (2013) (0)
Important Environmental Classes (2005) (0)
Reducing Planning Complexity of General Reinforcement Learning with Non-Markovian Abstractions (2021) (0)
Curiosity Killed or Incapacitated the Cat and the Asymptotically Optimal Agent (2020) (0)
Classification by decomposition: a novel approach to classification of symmetric $$2\times 2$$ games (2021) (0)
Treatise of Universal Induction (2011) (0)
Asymptotics of Continuous Bayes for Non-i.i.d. Sources (2014) (0)
How Useful are Hand-crafted Data? Making Cases for Anomaly Detection Methods (2021) (0)
Proceedings of the 9th European conference on Recent Advances in Reinforcement Learning (2011) (0)
Universal Agent Mixtures and the Geometry of Intelligence (2023) (0)
Practical Agents and Fundamental Challenges (2016) (0)
LMU 93-18 November 1993 Gluon Mass from Instantons (1993) (0)
Beyond Bayes-optimality: meta-learning what you know you don't know (2022) (0)
Asymptotics of Discrete MDL for Online Prediction. erratum (2017) (0)
The Mass of the 0 in selfdual QCD (1996) (0)
An Improved Bayesian Method for DNA Copy Number Estimation (2007) (0)
Algorithmic “Kolmogorov” Complexity (2008) (0)
An Analytical Approach to the BFS vs. DFS Algorithm Selection Problem 1 (2015) (0)
On the Optimality of General Reinforcement Learners (2015) (0)
Editors' Introduction (2010) (0)
Preface (2001) (0)
Kolmogorov Complexity and Applications, 29.01. - 03.02.2006 (2006) (0)
Chances and Risks of Artificial Intelligence—A Concept of Developing and Exploiting Machine Intelligence for Future Societies (2021) (0)
The Mass of the ' in selfdual QCD (1995) (0)
Preface [to] Theoretical Computer Science, Vol. 410 (19) (2009) (0)
Learning of k-CNF Boolean Functions (2015) (0)
Report on the Third Conference on Artificial General Intelligence (2010) (0)
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics: Preface (2007) (0)
Fully General Online Imitation Learning (2021) (0)
Reliable Point Correspondences in Scenes Dominated by Highly Reflective and Largely Homogeneous Surfaces (2014) (0)
Evaluating Representations with Readout Model Switching (2023) (0)
Statistical Machine Learning (2009) (0)
Method For Recognising An Activity In A Sequence Of Images (2019) (0)
Complexity Monotone in Conditions and Future Prediction Errors (2006) (0)
A Dual Process Theory of Optimistic Cognition - eScholarship (2014) (0)
Reinforcement Learning with Information-Theoretic Actuation (2021) (0)
Convergence and Loss Bounds for (2003) (0)
Short Tour Through the Book (2005) (0)
IDSIA-1106 General Discounting versus Average Reward (2006) (0)
Agents in Known Probabilistics Environments (2005) (0)
Universal Sequence Prediction (2005) (0)
The Decision Support System of PSI, and how it Meets the Needs of the Users (1997) (0)
Universal Compression of Piecewise i.i.d. Sources (2018) (0)
N ov 2 01 8 Performance Guarantees for Homomorphisms Beyond Markov Decision Processes (2018) (0)

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