# Peter Sunehag

According to our database

Collaborative distances:

^{1}, Peter Sunehag authored at least 45 papers between 2004 and 2018.Collaborative distances:

## Timeline

#### Legend:

Book In proceedings Article PhD thesis Other## Links

#### On csauthors.net:

## Bibliography

2018

Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward.

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Value-Decomposition Networks For Cooperative Multi-Agent Learning.

CoRR, 2017

2015

Rationality, optimism and guarantees in general reinforcement learning.

Journal of Machine Learning Research, 2015

Deep Reinforcement Learning with Attention for Slate Markov Decision Processes with High-Dimensional States and Actions.

CoRR, 2015

Reinforcement Learning in Large Discrete Action Spaces.

CoRR, 2015

Using Localization and Factorization to Reduce the Complexity of Reinforcement Learning.

Proceedings of the Artificial General Intelligence, 2015

2014

A Dual Process Theory of Optimistic Cognition.

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 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

2013

The Sample-Complexity of General Reinforcement Learning.

CoRR, 2013

Concentration and Confidence for Discrete Bayesian Sequence Predictors.

CoRR, 2013

On Nicod's Condition, Rules of Induction and the Raven Paradox.

CoRR, 2013

The Sample-Complexity of General Reinforcement Learning.

Proceedings of the 30th International Conference on Machine Learning, 2013

Online feature selection for Brain Computer Interfaces.

Proceedings of the 2013 IEEE Symposium on Computational Intelligence, 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

Q-learning for history-based reinforcement learning.

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Optimistic Agents are Asymptotically Optimal

CoRR, 2012

Adaptive Context Tree Weighting

CoRR, 2012

Feature Reinforcement Learning using Looping Suffix Trees.

Proceedings of the Tenth European Workshop on Reinforcement Learning, 2012

Asynchronous Brain Computer Interface using Hidden Semi-Markov Models.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Recursive channel selection techniques for brain computer interfaces.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012

Adaptive Context Tree Weighting.

Proceedings of the 2012 Data Compression Conference, Snowbird, UT, USA, April 10-12, 2012, 2012

Coding of Non-Stationary Sources as a Foundation for Detecting Change Points and Outliers in Binary Time-Series.

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

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

Context Tree Maximizing.

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

Principles of Solomonoff Induction and AIXI

CoRR, 2011

(Non-)Equivalence of Universal Priors

CoRR, 2011

Feature Reinforcement Learning In Practice

CoRR, 2011

Axioms for Rational Reinforcement Learning

CoRR, 2011

Sparse Kernel-SARSA(λ) with an Eligibility Trace.

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Gradient Based Algorithms with Loss Functions and Kernels for Improved On-Policy Control.

Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

Feature Reinforcement Learning in Practice.

Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 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

Axioms for Rational Reinforcement Learning.

Proceedings of the Algorithmic Learning Theory - 22nd International Conference, 2011

2010

Wearable sensor activity analysis using semi-Markov models with a grammar.

Pervasive and Mobile Computing, 2010

Consistency of Feature Markov Processes

CoRR, 2010

Consistency of Feature Markov Processes.

Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009

Variable Metric Stochastic Approximation Theory.

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Semi-Markov kMeans Clustering and Activity Recognition from Body-Worn Sensors.

Proceedings of the ICDM 2009, 2009

2007

Emerge and spread models and word burstiness.

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

2004

Subcouples of codimension one and interpolation of operators that almost agree.

Journal of Approximation Theory, 2004