Reinforcement learning guidance law of Q-learning.

As the intelligent missile being a major development trend, it is foreseeable that it will become a precise and effective strike weapon in the future battlefields. On the basis of the traditional proportional guidance saw, this paper proposes a guidance algorithm based on reinforcement learning with variable proportional coefficient. Taking the rate as the state, this algorithm designs a discretized action space, as well as a reward function based on the miss distance, to determine the correct guidance command for the missile. The simulation results prove the algorithm possesses better guidance accuracy than the traditional proportional guidance saw and endows the missile with the ability of autonomous decision-making. [ABSTRACT FROM AUTHOR]