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The advent of artificial intelligence technology paved the way of manyresearches to be made within air combat sector. Academicians and many otherresearchers did a research on a prominent research direction called autonomousmaneuver decision of UAV. Elaborative researches produced some outcomes, butdecisions that include Reinforcement Learning(RL) came out to be moreefficient. There have been many researches and experiments done to make anagent reach its target in an optimal way, most prominent are GeneticAlgorithm(GA) , A star, RRT and other various optimization techniques have beenused. But Reinforcement Learning is the well known one for its success. InDARPHA Alpha Dogfight Trials, reinforcement learning prevailed against a realveteran F16 human pilot who was trained by Boeing. This successor model wasdeveloped by Heron Systems. After this accomplishment, reinforcement learningbring tremendous attention on itself. In this research we aimed our UAV whichhas a dubin vehicle dynamic property to move to the target in two dimensionalspace in an optimal path using Twin Delayed Deep Deterministic Policy Gradients(TD3) and used in experience replay Hindsight Experience Replay(HER).We didtests on two different environments and used simulations.

Reinforcement Learning based Air Combat Maneuver Generation