Yes, it could simplify a lot of works.
The role of the Neural Network is to replace the need to set specific algorithms belonging to those kinds of specific behaviors that you list. All you need is to let your NN plays, learns from it’s loose or win.
For exemple, considering the game tanks, an action gives it a reward or not and the NN learns what actions give best reward only using the picture taken by only one camera in the scene.
The image could be other sensors, or for example in the case of robot, I actually use angles/quaternions in the robot arm.
What is interesting too, is to discover the capacity that our NN has to imagine new scenarios that noone envisages before.
What I observed too during training with tanks is that the NN learns quicker if you help it to win … for example by moving the other tank/target at a good place for getting a hit. It doesn’t matter for it if you moved or not the target. So I think it’s an example of what we will discover with NN inside games in the futur, and creating a good training could reveal a good experience of the game situations. How to win could become how to better train my NN.