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ATAL
2008
Springer
13 years 7 months ago
Adaptive Kanerva-based function approximation for multi-agent systems
In this paper, we show how adaptive prototype optimization can be used to improve the performance of function approximation based on Kanerva Coding when solving largescale instanc...
Cheng Wu, Waleed Meleis
TSMC
1998
135views more  TSMC 1998»
13 years 5 months ago
Universal stabilization using control Lyapunov functions, adaptive derivative feedback, and neural network approximators
— In this paper, the problem of stabilization of unknown nonlinear dynamical systems is considered. An adaptive feedback law is constructed that is based on the switching adaptiv...
Elias B. Kosmatopoulos
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
13 years 8 days ago
Adaptive bases for Q-learning
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Dotan Di Castro, Shie Mannor
SIAMCO
2002
121views more  SIAMCO 2002»
13 years 5 months ago
Consistent Approximations and Approximate Functions and Gradients in Optimal Control
As shown in [7], optimal control problems with either ODE or PDE dynamics can be solved efficiently using a setting of consistent approximations obtained by numerical discretizati...
Olivier Pironneau, Elijah Polak
SELMAS
2004
Springer
13 years 10 months ago
A Generative Approach for Multi-agent System Development
The development of Multi-Agent Systems (MASs) involves special concerns, such as interaction, adaptation, autonomy, among others. Many of these concerns are overlapping, crosscut e...
Uirá Kulesza, Alessandro F. Garcia, Carlos ...