bool user_input
uint16 number_of_population

# case if user_input is true
float32[] user_parameters # Length: number_of_dimensions * number_of_parameters_per_dimension
float32[] user_covariance_diag # Length: number_of_dimensions * number_of_parameters_per_dimension
float32[] current_cma_mean # Length: number_of_dimensions * number_of_parameters_per_dimension
float32[] conditional_points # Length: (number_of_dimensions + time_stamp[0,1]) * number_of_conditional_points
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)

# case if user_input is false
uint16 number_of_dimensions # this is the number of ProMPs * 2 (Position and Velocity)
uint16 number_of_parameters_per_dimensions
float32[] parameter_array # Length: number_of_population * number_of_dimensions * number_of_parameters_per_dimension
---
# response
float32[] parameter_array  # this is needed because in case of user input the parameters arent known yet
float32[] score