We use a genetic fuzzy logic approach for solving the aircraft conflict resolution problem. We consider a small uncertainty in the velocity and the maneuver parameters which causes each aircraft's position at any instant to be within a region of uncertainty represented by a convex hull. The objective is to find conflict-free trajectories for the aircraft that minimize the cost of maneuvers. This paper introduces our unique architecture that consists of a hidden layer of neurons and layer of Fuzzy Inference Systems (FISs). An artificial intelligence called EVE is used to train the system and once it is trained, its capability is evaluated on a set of test scenarios. We compare the cost and the computational time of our approach with that obtained by directly applying Genetic Algorithm (GA). The results show the effectiveness of our approach in finding quick near-optimal solutions.