Alexander L. Strehl

Affiliations:
  • Rutgers University, USA


According to our database1, Alexander L. Strehl authored at least 23 papers between 2004 and 2017.

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Bibliography

2017
Associative Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning and Data Mining, 2017

2011
Knows what it knows: a framework for self-aware learning.
Mach. Learn., 2011

2010
Associative Reinforcement Learning.
Proceedings of the Encyclopedia of Machine Learning, 2010

Learning from Logged Implicit Exploration Data
CoRR, 2010

Learning from Logged Implicit Exploration Data.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Reinforcement Learning in Finite MDPs: PAC Analysis.
J. Mach. Learn. Res., 2009

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

Conditional Probability Tree Estimation Analysis and Algorithms.
Proceedings of the UAI 2009, 2009

2008
An analysis of model-based Interval Estimation for Markov Decision Processes.
J. Comput. Syst. Sci., 2008

Predictive Indexing for Fast Search.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Probably Approximately Correct (PAC) Exploration in Reinforcement Learning.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Exploration scavenging.
Proceedings of the Machine Learning, 2008

Expediting RL by using graphical structures.
Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 2008

2007
Online Linear Regression and Its Application to Model-Based Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Efficient Structure Learning in Factored-State MDPs.
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence, 2007

2006
Incremental Model-based Learners With Formal Learning-Time Guarantees.
Proceedings of the UAI '06, 2006

Experience-efficient learning in associative bandit problems.
Proceedings of the Machine Learning, 2006

PAC model-free reinforcement learning.
Proceedings of the Machine Learning, 2006

A hierarchical approach to efficient reinforcement learning in deterministic domains.
Proceedings of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2006), 2006

2005
Efficient Exploration With Latent Structure.
Proceedings of the Robotics: Science and Systems I, 2005

A theoretical analysis of Model-Based Interval Estimation.
Proceedings of the Machine Learning, 2005

2004
Ternary codes through ternary designs.
Australas. J Comb., 2004

An Empirical Evaluation of Interval Estimation for Markov Decision Processes.
Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2004), 2004


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