18 lines
1.1 KiB
Plaintext
18 lines
1.1 KiB
Plaintext
bool user_input
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uint16 number_of_population
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# case if user_input is true
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float32[] user_parameters # Length: number_of_dimensions * number_of_parameters_per_dimension
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float32[] user_covariance_diag # Length: number_of_dimensions * number_of_parameters_per_dimension
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float32[] current_cma_mean # Length: number_of_dimensions * number_of_parameters_per_dimension
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float32[] conditional_points # Length: (number_of_dimensions + time_stamp[0,1]) * number_of_conditional_points
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float32 weight_parameter # this parameter sets the weighted average 0 dont trust user 1 completly trust user (it is set by the user or it is decays over time i have to do some experiments on that)
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# case if user_input is false
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uint16 number_of_dimensions # this is the number of ProMPs * 2 (Position and Velocity)
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uint16 number_of_parameters_per_dimensions
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float32[] parameter_array # Length: number_of_population * number_of_dimensions * number_of_parameters_per_dimension
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---
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# response
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float32[] parameter_array # this is needed because in case of user input the parameters arent known yet
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float32[] score |