Shivaram's Reading List


Function Approximation     Partial Observability     Learning Methods     Ensembles    
Stochastic Optimisation     General RL     General ML     Multiagent Learning    
Comparison/Integration     Bandits     Applications     Robot Soccer    
Humanoids     Parameter     MDP     Empirical    
Failure Warning     Representation     General AI     Neural Networks    
All    

Stochastic Optimisation

Simulation optimization using the cross-entropy method with optimal computing budget allocation
Donghai He, Loo Hay Lee, Chun-Hung Chen, Michael C. Fu, and Segev Wasserkrug, 2010
Details   

The Knowledge-Gradient Policy for Correlated Normal Beliefs
Peter Frazier, Warren Powell, and Savas Dayanik, 2009
Details   

Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search
Verena Heidrich-Meisner and Christian Igel, 2009
Details   

Stochastic search using the natural gradient
Yi Sun, Daan Wierstra, Tom Schaul, and Jürgen Schmidhuber, 2009
Details   

Integrating Techniques from Statistical Ranking into Evolutionary Algorithms
Christian Schmidt, Jürgen Branke, and Stephen E. Chick, 2006
Details   

Sequential Sampling in Noisy Environments
Jürgen Branke and Christian Schmidt, 2004
Details   

Introduction to Stochastic Search and Optimization
James C. Spall, 2003
Details   

Threshold selection, hypothesis tests, and DOE methods
Thomas Beielstein and Sandor Markon, 2002
Details   

Optimization for simulation: Theory vs. Practice
Michael C. Fu, 2002
Details   

Evolution strategies in noisy environments- a survey of existing work
D. V. Arnold, 2001
Details   

Thresholding - a selection operator for noisy ES
Sandor Markon, Dirk V. Arnold, Thomas Bäck, Thomas Beielstein, and Hans-Georg Beyer, 2001
Details   

Evolutionary algorithms in noisy environments: theoretical issues and guidelines for practice
Hans-Georg Beyer, 2000
Details   

Optimization of Noisy Fitness Functions by Means of Genetic Algorithms Using History of Search
Yasuhito Sano and Hajime Kita, 2000
Details   

Q2: Memory-Based Active Learning for Optimizing Noisy Continuous Functions
Andrew W. Moore, Jeff G. Schneider, Justin A. Boyan, and Mary S. Lee, 1998
Details   

Averaging Efficiently in the Presence of Noise
Peter Stagge, 1998
Details   

The Racing Algorithm: Model Selection for Lazy Learners
Oded Maron and Andrew W. Moore, 1997
Details   

Simulated Annealing for noisy cost functions
Walter J. Gutjahr and Georg Ch. Pflug, 1996
Details   

Genetic Algorithms, Selection Schemes, and the Varying Effects of Noise
Brad L. Miller and David E. Goldberg, 1996
Details   

Memory-based Stochastic Optimization
Andrew W. Moore and Jeff Schneider, 1996
Details   

Genetic algorithms in noisy environments
J. Michael Fitzpatrick and John J. Grefenstette, 1988
Details