This paper mainly focuses on investigating the discrete event dynamic decision-making process with two noncooperative intelligent agents, defined as event dynamic games (EDGs). We introduce a novel state space model and analyze the existence of its equilibrium solution. Additionally, we apply principles of network evolution to address the challenge of event dynamic game network modeling. By providing a normal-form strategic model, we first establish a game tree evolution model, which serves as an extended expression and more accurately captures the impact of changes in event strategies on the game process. Furthermore, we conduct an in-depth analysis of the multi-layered temporal evolution behaviors exhibited by EDGs and develop a corresponding network evolution model. Finally, the validity of the proposed model is demonstrated through application examples, along with a detailed analysis of the cooperative behaviors of nodes during the evolution process.
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