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NIPS
2003
15 years 8 months ago
Gaussian Processes in Reinforcement Learning
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
Carl Edward Rasmussen, Malte Kuss
AAAI
2000
15 years 8 months ago
Divide-and-Conquer Frontier Search Applied to Optimal Sequence Alignment
We present a new algorithm that reduces the space complexity of heuristic search. It is most effective for problem spaces that grow polynomially with problem size, but contain lar...
Richard E. Korf, Weixiong Zhang
ENTCS
2006
151views more  ENTCS 2006»
15 years 6 months ago
Stochastic Simulation Methods Applied to a Secure Electronic Voting Model
We demonstrate a novel simulation technique for analysing large stochastic process algebra models, applying this to a secure electronic voting system example. By approximating the...
Jeremy T. Bradley, Stephen T. Gilmore
COMGEO
2007
ACM
15 years 6 months ago
An incremental algorithm for reconstruction of surfaces of arbitrary codimension
A new algorithm is presented for surface reconstruction from unorganized points. Unlike many previous algorithms, this algorithm does not select a subcomplex of the Delaunay Trian...
Daniel Freedman
EC
2000
171views ECommerce» more  EC 2000»
15 years 6 months ago
Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions
Building blocks are a ubiquitous feature at all levels of human understanding, from perception through science and innovation. Genetic algorithms are designed to exploit this prev...
John H. Holland