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ICML
2006
IEEE
16 years 2 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
NIPS
2008
15 years 3 months ago
Optimization on a Budget: A Reinforcement Learning Approach
Many popular optimization algorithms, like the Levenberg-Marquardt algorithm (LMA), use heuristic-based "controllers" that modulate the behavior of the optimizer during ...
Paul Ruvolo, Ian R. Fasel, Javier R. Movellan
PEWASUN
2006
ACM
15 years 7 months ago
Experimental analysis of a transport protocol for ad hoc networks (TPA)
Many previous papers have pointed out that TCP performance in multi-hop ad hoc networks is not optimal. This is due to several TCP design principles that reflect the characteristi...
Giuseppe Anastasi, Emilio Ancillotti, Marco Conti,...
HEURISTICS
2008
120views more  HEURISTICS 2008»
15 years 1 months ago
A local linear embedding module for evolutionary computation optimization
A Local Linear Embedding (LLE) module enhances the performance of two Evolutionary Computation (EC) algorithms employed as search tools in global optimization problems. The LLE em...
Fabio Boschetti
CDC
2008
IEEE
109views Control Systems» more  CDC 2008»
15 years 8 months ago
MPC for tracking with optimal closed-loop performance
— This paper deals with the tracking problem for constrained linear systems using a model predictive control (MPC) law. As it is well known, MPC provides a control law suitable f...
Antonio Ferramosca, Daniel Limón, Ignacio A...