We have looked extensively at external or extrinsic rewards for several chapters now and how techniques can be used to optimize and encourage them for agents. Now, it may seem like the easy way to go in order to modify an agent's behavior is by altering its extrinsic rewards or in essence its reward functions. However, this can be prone to difficulties, and this can often alter training performance for the worse, which is what we witnessed when we added Curriculum Learning (CL) to a couple of agents in the previous section. Of course, even if we make the training worse, we now have a number of techniques up our sleeves such as Transfer Learning (TL), also known as Imitation Learning (IL); Curiosity; and CL, to help us correct things.
In the next exercise, we are going to look to add further individuality to our agents by adding additional...
