Search alternatives:
algorithm sphere » algorithm where (Expand Search), algorithm pre (Expand Search), algorithm shows (Expand Search)
sphere function » severe functional (Expand Search), reserve function (Expand Search)
value function » rate function (Expand Search), wave function (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
algorithm sphere » algorithm where (Expand Search), algorithm pre (Expand Search), algorithm shows (Expand Search)
sphere function » severe functional (Expand Search), reserve function (Expand Search)
value function » rate function (Expand Search), wave function (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
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Results of searching performance of different algorithm models on the Sphere function and Griewank function.
Published 2021“…<p>Results of searching performance of different algorithm models on the Sphere function and Griewank function.…”
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Completion times for different algorithms.
Published 2025“…Action masking is used to filter out invalid states and actions, while a shared reward mechanism is adopted to balance cooperation efficiency among agents. Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”
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The average cumulative reward of algorithms.
Published 2025“…Action masking is used to filter out invalid states and actions, while a shared reward mechanism is adopted to balance cooperation efficiency among agents. Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”
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Simulation settings of rMAPPO algorithm.
Published 2025“…Action masking is used to filter out invalid states and actions, while a shared reward mechanism is adopted to balance cooperation efficiency among agents. Additionally, value function normalization and adaptive learning rate strategies are applied to accelerate convergence. …”
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Algorithm of the brightness scale calibration experiment.
Published 2024“…The “level” denotes the number of perceptually equal units of brightness, while the scale is an array storing brightness vs. luminous intensity function values.</p>…”
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