Method for automatically setting at least one parameter (θ) of an actuator control system , which is set up for controlling a control variable (x) of an actuator to a predefinable target value (xd), wherein the actuator control system is set up, depending on the at least one parameter (θ), the target value (xd) and the control variable (x) to generate a manipulated variable (u) and depending on this manipulated variable (u) to control the actuator , wherein a new value (θ*) of the at least one parameter (θ) is selected depending on a long-term cost function, R, wherein this long-term cost function, R, is determined depending on a predicted temporal evolution of a probability distribution, p, of the control variable (x) of the actuator and the parameter (θ) is then set to this new value (θ*), characterized in that the predicted temporal evolution of the probability distribution, p, of the control variable (x) is determined by an approximation of an integration over possible values of the control variable (x), this approximation being done through numerical quadrature, wherein the numeric quadrature approximates the integral by evaluating the integrand at supporting points (ξ) and support weights associated with the supporting points (ξ); wherein a density of supporting points (ξ) being determined as a function of a determined first temporal evolution, τ1 ... τT , of the control variable (x), in particular determined by means of the model, g, and/or the actuator control system , starting from an initial value, τ0, of the control variable (x) determined at random from an initial probability distribution, p(x0), wherein the density of the supporting points (ξ) is also determined as a determined second temporal evolution, τ'0 ... τ'T, of the control variable (x), in particular determined by means of the model, g, and/or the actuator control system , starting from the setpoint value (xd) as initial value, τ'0, of the control variable (x), wherein a density of the supporting points (ξ) is selected as a function of a quantity (Var) which characterizes a smoothness of the model, g, at at least one value, τ0 ... τ'T, τ'0 ... τ'T, of the control variable (x) in the determined temporal evolution or evolutions of the control variable (x). the predicted temporal evolution of the probability distribution, p, of the control variable (x) is determined by an approximation of an integration over possible values of the control variable (x), this approximation being done through numerical quadrature, wherein the numeric quadrature approximates the integral by evaluating the integrand at supporting points (ξ) and support weights associated with the supporting points (ξ); wherein a density of supporting points (ξ) being determined as a function of a determined first temporal evolution, τ1 ... τT , of the control variable (x), in particular determined by means of the model, g, and/or the actuator control system , starting from an initial value, τ0, of the control variable (x) determined at random from an initial probability distribution, p(x0), wherein the density of the supporting points (ξ) is also determined as a determined second temporal evolution, τ'0 ... τ'T, of the control variable (x), in particular determined by means of the model, g, and/or the actuator control system , starting from the setpoint value (xd) as initial value, τ'0, of the control variable (x), wherein a density of the supporting points (ξ) is selected as a function of a quantity (Var) which characterizes a smoothness of the model, g, at at least one value, τ0 ... τ'T, τ'0 ... τ'T, of the control variable (x) in the determined temporal evolution or evolutions of the control variable (x). <EOS>