  The advent of artificial intelligence technology paved the way of many
researches to be made within air combat sector. Academicians and many other
researchers did a research on a prominent research direction called autonomous
maneuver decision of UAV. Elaborative researches produced some outcomes, but
decisions that include Reinforcement Learning(RL) came out to be more
efficient. There have been many researches and experiments done to make an
agent reach its target in an optimal way, most prominent are Genetic
Algorithm(GA) , A star, RRT and other various optimization techniques have been
used. But Reinforcement Learning is the well known one for its success. In
DARPHA Alpha Dogfight Trials, reinforcement learning prevailed against a real
veteran F16 human pilot who was trained by Boeing. This successor model was
developed by Heron Systems. After this accomplishment, reinforcement learning
bring tremendous attention on itself. In this research we aimed our UAV which
has a dubin vehicle dynamic property to move to the target in two dimensional
space in an optimal path using Twin Delayed Deep Deterministic Policy Gradients
(TD3) and used in experience replay Hindsight Experience Replay(HER).We did
tests on two different environments and used simulations.
