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ICML
2004
IEEE
16 years 6 months ago
Learning and discovery of predictive state representations in dynamical systems with reset
Predictive state representations (PSRs) are a recently proposed way of modeling controlled dynamical systems. PSR-based models use predictions of observable outcomes of tests that...
Michael R. James, Satinder P. Singh
ICML
2001
IEEE
16 years 6 months ago
Convergence of Gradient Dynamics with a Variable Learning Rate
As multiagent environments become more prevalent we need to understand how this changes the agent-based paradigm. One aspect that is heavily affected by the presence of multiple a...
Michael H. Bowling, Manuela M. Veloso
ICML
2000
IEEE
16 years 6 months ago
A Nonparametric Approach to Noisy and Costly Optimization
This paper describes Pairwise Bisection: a nonparametric approach to optimizing a noisy function with few function evaluations. The algorithm uses nonparametric reasoning about si...
Brigham S. Anderson, Andrew W. Moore, David Cohn
ICML
2000
IEEE
16 years 6 months ago
A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets
This paper has no novel learning or statistics: it is concerned with making a wide class of preexisting statistics and learning algorithms computationally tractable when faced wit...
Paul Komarek, Andrew W. Moore
ICML
2000
IEEE
16 years 6 months ago
Combining Reinforcement Learning with a Local Control Algorithm
We explore combining reinforcement learning with a hand-crafted local controller in a manner suggested by the chaotic control algorithm of Vincent, Schmitt and Vincent (1994). A c...
Andrew G. Barto, Jette Randløv, Michael T. ...