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CCE
2004
15 years 5 months ago
Improving convergence of the stochastic decomposition algorithm by using an efficient sampling technique
This work focuses on the basic stochastic decomposition (SD) algorithm of Higle and Sen [J.L. Higle, S. Sen, Stochastic Decomposition, Kluwer Academic Publishers, 1996] for two-st...
José María Ponce-Ortega, Vicente Ric...
HYBRID
2009
Springer
16 years 22 days ago
Convergence of Distributed WSN Algorithms: The Wake-Up Scattering Problem
In this paper, we analyze the problem of finding a periodic schedule for the wake-up times of a set of nodes in a Wireless Sensor Network that optimizes the coverage of the region...
Daniele Fontanelli, Luigi Palopoli, Roberto Passer...
MP
2007
102views more  MP 2007»
15 years 5 months ago
Elastic-mode algorithms for mathematical programs with equilibrium constraints: global convergence and stationarity properties
The elastic-mode formulation of the problem of minimizing a nonlinear function subject to equilibrium constraints has appealing local properties in that, for a finite value of the...
Mihai Anitescu, Paul Tseng, Stephen J. Wright
ICML
1996
IEEE
15 years 10 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos
ICML
2003
IEEE
16 years 6 months ago
AWESOME: A General Multiagent Learning Algorithm that Converges in Self-Play and Learns a Best Response Against Stationary Oppon
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
Vincent Conitzer, Tuomas Sandholm