During my previous research, I have implemented SWARM algorithms based on ant colonies and bird flying motion, which are capable of find optimal solution for the well-known NP-hard Travelling salesman problem. In my current thesis, I present the deployment of unique SWARM algorithms based on the previously implemented methods, and the drafts of the repair and tuning procedures integrated fuzzy and Game theory mechanisms for creating effective high-level cooperative military team-strategies. I introduce the Art of War v6.0 simulator - designed by Peter Kisfaludi and Lajos Szarka - created for the military game enviroment simulation. I detail the basic SWARM hybrid method – constructed by me in the last year -, and the complex platform exploring method based on multi-level potential-fields, which proved its advantages with the dynamic parameter tuning. Additionally I will introduce a multi-dimensional data structure, which will have a main role in buffering and calculating the result of fuzzy functions, and help effectively finding the Nash-equilibriums according to my future plans of deployment.