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We propose a framework of robust approximate dynamic programming (robust-ADP), which is aimed at computing globally asymptotically stabilizing, suboptimal, control laws with robustness to dynamic uncertainties, via on-line/off-line learning. The system studied in this paper is an interconnection of a linear model with fully measurable state and unknown dynamics, and a nonlinear system with unmeasured...
This paper studies the stochastic optimal control problem with additive and multiplicative noise via reinforcement learning (RL) and approximate/adaptive dynamic programming (ADP). Using Itô calculus, a policy iteration algorithm is derived in the presence of both additive and multiplicative noise. It is shown that the expectation of the approximated cost matrix is guaranteed to converge to the solution...
The High Assurance Internet Protocol Encrypt or (HAIPE) Interoperability Specification is developed by the US Department of Defense to permit enclaves equipped with compliant gateways to communicate securely over un-trusted networks. Using Cryptographic Key Agreement protocol, e.g., Internet Key Exchange (IKE), HAIPEs can establish automated security associations (SA) for this device instead of manually...
TSK fuzzy model is decomposed into two different populations to cooperate coevolution model learning technique for its learning is the problems of multiple constraints and multiple target optimizations. All the related problems are discussed, including encode, evolution calculation, cooperation of every population and evaluation strategy of adaptive value. The technique presented has merits in little...
How to reduce the measurement error caused by linear regression is the key in measuring tea moisture content with microwave transmission techniques. In this paper, an improved BP algorithm, which combines the genetic algorithm, is given for training artificial neural network to get the range of weights and thresholds. The method makes BP algorithm avoid getting into infinitesimal locally and has the...
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