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TSMC
2008
140views more  TSMC 2008»
13 years 9 months ago
Adaptive Feedback Control by Constrained Approximate Dynamic Programming
A constrained approximate dynamic programming (ADP) approach is presented for designing adaptive neural network (NN) controllers with closed-loop stability and performance guarante...
S. Ferrari, J. E. Steck, R. Chandramohan
ICML
2006
IEEE
14 years 3 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
AAAI
2006
13 years 11 months ago
Learning Basis Functions in Hybrid Domains
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...
Branislav Kveton, Milos Hauskrecht
SIAMJO
2008
72views more  SIAMJO 2008»
13 years 9 months ago
A Sample Approximation Approach for Optimization with Probabilistic Constraints
We study approximations of optimization problems with probabilistic constraints in which the original distribution of the underlying random vector is replaced with an empirical dis...
James Luedtke, Shabbir Ahmed
CEC
2010
IEEE
13 years 1 months ago
A hybrid genetic algorithm for rescue path planning in uncertain adversarial environment
— Efficient vehicle path planning in hostile environment to carry out rescue or tactical logistic missions remains very challenging. Most approaches reported so far relies on key...
Jean Berger, Khaled Jabeur, Abdeslem Boukhtouta, A...