In the following, I put the link for the general algorithm of maximum entropy inverse reinforcement learning. http://184.108.40.206/assets/maxent/maxent_slide.jpg
This uses a gradient descent algorithm. The point that I do not understand is there is only a single gradient value and it is used to update a vector of parameters. To me, it does not make sense because it is updating all elements of a vector with the same value. Can you explain the logic behind updating a vector with a single gradient?