the feature function as 0 1 if you pick up a triangle and now you can and we define it as we define it as 0 0 if you pick up nothing and now you can fairly easily see that the reward of each task can be simply calculated by mixing the features accordingly okay so reward one is going to be simply the feature a 1 0 which is the w vector so i can specify a task by giving the appropriate w vector and now you can see that if this is my reward function my agent can go out into the world if it collects a square it is going to