Shane Legg

According to our database1, Shane Legg authored at least 41 papers between 2004 and 2018.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
Modeling Friends and Foes.
CoRR, 2018

Measuring and avoiding side effects using relative reachability.
CoRR, 2018

Agents and Devices: A Relative Definition of Agency.
CoRR, 2018

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.
CoRR, 2018

Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents.
CoRR, 2018

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
AI Safety Gridworlds.
CoRR, 2017

Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017.
CoRR, 2017

Symmetric Decomposition of Asymmetric Games.
CoRR, 2017

Deep reinforcement learning from human preferences.
CoRR, 2017

Noisy Networks for Exploration.
CoRR, 2017

Reinforcement Learning with a Corrupted Reward Channel.
CoRR, 2017

Deep Reinforcement Learning from Human Preferences.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Reinforcement Learning with a Corrupted Reward Channel.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Soft-Bayes: Prod for Mixtures of Experts with Log-Loss.
Proceedings of the International Conference on Algorithmic Learning Theory, 2017

2016
DeepMind Lab.
CoRR, 2016

2015
Human-level control through deep reinforcement learning.
Nature, 2015

Massively Parallel Methods for Deep Reinforcement Learning.
CoRR, 2015

Letter to the Editor: Research Priorities for Robust and Beneficial Artificial Intelligence: An Open Letter.
AI Magazine, 2015

2014
From academia to industry: The story of Google DeepMind.
Proceedings of the 2014 Imperial College Computing Student Workshop, 2014

2011
An Approximation of the Universal Intelligence Measure
CoRR, 2011

An Approximation of the Universal Intelligence Measure.
Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011

2008
Temporal Difference Updating without a Learning Rate
CoRR, 2008

2007
Algorithmic probability.
Scholarpedia, 2007

Universal Intelligence: A Definition of Machine Intelligence.
Minds and Machines, 2007

Tests of Machine Intelligence
CoRR, 2007

Universal Intelligence: A Definition of Machine Intelligence
CoRR, 2007

A Collection of Definitions of Intelligence
CoRR, 2007

Temporal Difference Updating without a Learning Rate.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

2006
Fitness uniform optimization.
IEEE Trans. Evolutionary Computation, 2006

Fitness Uniform Optimization
CoRR, 2006

Is there an Elegant Universal Theory of Prediction?
CoRR, 2006

A Formal Measure of Machine Intelligence
CoRR, 2006

Is There an Elegant Universal Theory of Prediction?
Proceedings of the Algorithmic Learning Theory, 17th International Conference, 2006

Tests of Machine Intelligence.
Proceedings of the 50 Years of Artificial Intelligence, 2006

A Collection of Definitions of Intelligence.
Proceedings of the Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms, 2006

2005
Fitness Uniform Deletion: A Simple Way to Preserve Diversity
CoRR, 2005

A Universal Measure of Intelligence for Artificial Agents.
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.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005

2004
Tournament versus Fitness Uniform Selection
CoRR, 2004

Tournament versus fitness uniform selection.
Proceedings of the IEEE Congress on Evolutionary Computation, 2004


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