Sciweavers

340 search results - page 41 / 68
» Kernelized value function approximation for reinforcement le...
Sort
View
ML
2008
ACM
152views Machine Learning» more  ML 2008»
15 years 2 months ago
Learning near-optimal policies with Bellman-residual minimization based fitted policy iteration and a single sample path
Abstract. We consider batch reinforcement learning problems in continuous space, expected total discounted-reward Markovian Decision Problems. As opposed to previous theoretical wo...
András Antos, Csaba Szepesvári, R&ea...
ICAC
2006
IEEE
15 years 8 months ago
A Hybrid Reinforcement Learning Approach to Autonomic Resource Allocation
— Reinforcement Learning (RL) provides a promising new approach to systems performance management that differs radically from standard queuing-theoretic approaches making use of ...
Gerald Tesauro, Nicholas K. Jong, Rajarshi Das, Mo...
ALT
2004
Springer
15 years 11 months ago
On Kernels, Margins, and Low-Dimensional Mappings
Kernel functions are typically viewed as providing an implicit mapping of points into a high-dimensional space, with the ability to gain much of the power of that space without inc...
Maria-Florina Balcan, Avrim Blum, Santosh Vempala
ICRA
1994
IEEE
105views Robotics» more  ICRA 1994»
15 years 6 months ago
Harmonic Functions and Collision Probabilities
There is a close relationship between harmonic functions { which have recently been proposed for path planning { and hitting probabilities for random processes. The hitting probab...
Christopher I. Connolly
96
Voted
IJCNN
2006
IEEE
15 years 8 months ago
Learning to Rank by Maximizing AUC with Linear Programming
— Area Under the ROC Curve (AUC) is often used to evaluate ranking performance in binary classification problems. Several researchers have approached AUC optimization by approxi...
Kaan Ataman, W. Nick Street, Yi Zhang