Research on the Equilibrium Strategy of UAV Attack and Defense Game Based on MCCFVFP

The unmanned aerial vehicle (UAV) attack and defense (A&D) confrontation can be modeled as a game problem. However, existing research does not fully consider the incompleteness of game information, making it difficult to apply in complex and unknown UAV A&D scenarios. Game theory provides a tool for the modeling and analysis of UAV A&D. Firstly, this paper establishes an incomplete information dynamic game model for UAV A&D and abstracts the scenario to simplify the complex environment and UAV movement. Secondly, an improved Counterfactual Regret Minimization algorithm is introduced to solve the model. Through Monte Carlo sampling, the efficiency of solving complex game problems is improved. Finally, the equilibrium strategy obtained from the solution is verified by experimental simulation, effectively demonstrating the feasibility and effectiveness of the algorithm.