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69
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CDC
2008
IEEE
204views Control Systems» more  CDC 2008»
15 years 4 months ago
Dynamic ping optimization for surveillance in multistatic sonar buoy networks with energy constraints
— In this paper we study the problem of dynamic optimization of ping schedule in an active sonar buoy network deployed to provide persistent surveillance of a littoral area throu...
Anshu Saksena, I-Jeng Wang
87
Voted
ICRA
2008
IEEE
173views Robotics» more  ICRA 2008»
15 years 4 months ago
Bayesian reinforcement learning in continuous POMDPs with application to robot navigation
— We consider the problem of optimal control in continuous and partially observable environments when the parameters of the model are not known exactly. Partially Observable Mark...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
NIPS
2003
14 years 11 months ago
A Nonlinear Predictive State Representation
Predictive state representations (PSRs) use predictions of a set of tests to represent the state of controlled dynamical systems. One reason why this representation is exciting as...
Matthew R. Rudary, Satinder P. Singh
65
Voted
EOR
2006
66views more  EOR 2006»
14 years 9 months ago
Performance prediction of an unmanned airborne vehicle multi-agent system
Consider unmanned airborne vehicle (UAV) control agents in a dynamic multi-agent system. The agents must have a set of goals such as destination airport and intermediate positions...
Zhaotong Lian, Abhijit Deshmukh
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 7 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel