Learning the task execution steps for a target goal
Input - A Target Goal (e.g. Go To Cinema Hall)
Output - A sequence of steps (e.g. Go To Bus Stop -&gt; Onboard A Bus -&gt; Drop at Location X -&gt; Walk 100 meters.

I assume that there's no other information available to the model, such as geographical information about the possible locations (i.e. the training data is made only of examples objective + sequence). As far as I can tell this implies that there's no way to use similarity between two objectives, since there's no way to know if similar places are in the same area.
Under this definition, the objective is a single categorical variable. So there's just nothing to learn except mapping an objective with its corresponding sequence, no need for ML at all: just store the list which maps any objective in the training data to its corresponding sequence in a map (dictionary).