After finding a great pathfinding plug-in and figuring out that is is most likely the best discussion to create levels via Blender, I finally started to play around with AI.

I made an simple and small neural network using states of the AI as Output and own health and targets health as Input.


Basically it works like this:

(At the beginning a random state will be selected)

The AI's goal is it to exterminate! it's target.

The AI's individual states (OUTPUTS) uses points (high points happy, low points unhappy).
Certain Factors will influence (add and detract) points from the current (active) state.

After a certain break point the AI will switch to the state with the highest points (if the current state is still the highest, it will remain).

The AI's states (OUTPUTS) are:
1. stand,
2. walk towards target,
3. walk away from target,
4. strafe (left or right) ,
4. stay out of sight of the target, but approach,
5. stay out of sight of the target, and keep distance,
6. stay put,
7. run to nearest cover.

Factors (INPUT) that add or detract points are:
1. target losses health ++points,
2. AI losses heath --points,
4. being traced (aimed at) -points,
5. not able to trace target for some time (state 2 is an exception) -points (prevent stalemate ),
6. being able to trace the target itself +points.


Does anybody see any flaws here, or potential stalemates?
How would you improve on this?


Looking forward for an interesting discussion ^^


PS: And remind me to finish that cover system so I can share it.