Algorithm 2: Jamming effectiveness evaluation algorithm

Input: Evaluation indicator vector ${\mathit{x}}^{\left(k\right)}$

Output: Jamming effect evaluation result $R_o^{\left(k\right)}$

Calculate the Euclidean distance $d({\mathit{x}}^{(k-1)},{\mathit{x}}^{\left(k\right)},{\mathbf{\omega }}^{\left(k\right)})$ between normalized ${\mathit{x}}^{\left(k\right)}$ and   the last indicator vector ${\mathit{x}}^{(k-1)}$ with the weight vector ${\mathbf{\omega }}^{\left(k\right)}$ according to Equation (14)

Calculate the feedback $R_o^{\left(k\right)}$ of the DQL model through Equation (15).