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Showing 1 to 7 of 7 for “"Matrix Adaptation Evolution Strategy"”.
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Selecting appropriate reinforcement-learning algorithms for robot manipulation domains
… reinforcement learning algorithms: Covariance Matrix Adaptation Evolution Strategy, Deep Deterministic Policy Gradients, and Proximal Policy Optimization. We compare their performance on various target domains to measure quantitatively their dependence on varied features of the environment. We …
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Multi-objective evolutionary algorithms for product design
… Chemistry and Machine Learning (ML) with Evolutionary MultiObjective Optimisation (EMOO) techniques to streamline compound design. This approach automates the design process by leveraging ML to accurately predict compound properties and using EMOO to select compounds that meet various …
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Measurement of ignition delay time of jet fuels in shock tube for the development of the chemical kinetic mechanism
… for a cycloalkane-rich CycloSAF. A Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is then employed to optimize selected Arrhenius parameters of the 16 lumped HyChem reactions using a multi-objective function that combines ignition-delay RMSE and L1/L2-type regularization, with tight …
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Design problem optimization with multi-objective evolutionary algorithms
… and comparing two advanced multi-objective evolutionary algorithms—Multi-Objective Covariance Matrix Adaptation Evolution Strategy (MOCMA-ES) and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II)—to optimize sunshades across five key objectives: thermal comfort, energy consumption, …
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2D-3D Registration Methods for Computer-Assisted Orthopaedic Surgery
… Unscented Kalman Filter (UKF) and Covariance Matrix Adaptation Evolution Strategy (CMA-ES), to improve the capture range for the 2D-3D registration problem; 2) a multiple-object 2D-3D registration technique is proposed that simultaneously aligns multiple 3D images of fracture fragments to a …
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Dynamic identification of the Augusta hybrid base isolated building using data from full scale push and sudden release tests
… in the time domain using the Covariance Matrix Adaptation Evolution Strategy, a stochastic algorithm for difficult, non linear black-box optimization. The identification of the isolation system provided the mass of the rigid block, the bi-linear properties used in the mechanical …
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Evolutionary Algorithm For Large-Scale Optimization
… function. To deal with these issues, several Evolutionary Algorithms (EAs) based on the divide-and-conquer concept have been proposed. A popular approach in this area is Cooperative Co-evolution (CC) which usually divides a problem into a number of smaller sub-problems that can be optimized …