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NIPS
2008
13 years 9 months ago
Bayesian Network Score Approximation using a Metagraph Kernel
Many interesting problems, including Bayesian network structure-search, can be cast in terms of finding the optimum value of a function over the space of graphs. However, this fun...
Benjamin Yackley, Eduardo Corona, Terran Lane
CDC
2008
IEEE
115views Control Systems» more  CDC 2008»
14 years 1 months ago
Min-Max predictive control of a pilot plant using a QP approach
— The practical implementation of Min-Max MPC (MMMPC) controllers is limited by the computational burden required to compute the control law. This problem can be circumvented by ...
Jorn Klaas Gruber, Daniel R. Ramírez, Teodo...
CCIA
2005
Springer
14 years 1 months ago
Direct Policy Search Reinforcement Learning for Robot Control
— This paper proposes a high-level Reinforcement Learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, whe...
Andres El-Fakdi, Marc Carreras, Narcís Palo...
ICML
2006
IEEE
14 years 1 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
ESANN
2004
13 years 8 months ago
High-accuracy value-function approximation with neural networks applied to the acrobot
Several reinforcement-learning techniques have already been applied to the Acrobot control problem, using linear function approximators to estimate the value function. In this pape...
Rémi Coulom