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In this paper, we combine a spherical coordinate method and a gradient learning optimization algorithm to solve the dynamic power management (DPM) problem. In our approach, the DPM is modeled as a constrained SMDP problem with unknown model parameters. By utilizing an augmented Lagrange multiplier method, we provide an online optimization method for the DPM. This method may estimate the gradient of...
Workspace is an important performance index for robotic manipulators. There have been numerous literatures on all aspects of it. This work aims to provide a full picture of workspace. An extensive review of manipulator workspace is presented in this paper, including classification, determination and analysis of workspace. Along with rapid progress of computer's computation performance, the manipulator...
On the basis of the sensitivity-based optimization, we develop a unified optimization approach for semi-Markov decision processes (SMDPs) with infinite horizon discounted and average reward criteria. We show that the sensitivity formula under average reward criteria is a limitation case of discounted reward criteria. On the basis of the performance sensitivity formulas, we provide a unified formulation...
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