This article investigates the optimal control strategy problem for nonzero-sum games of the immune system based on adaptive dynamic programming (ADP). First, the main objective is approximating a Nash equilibrium between the tumor cells and the immune cell population, which is governed through chemotherapy drugs and immunoagents guided by the mathematical growth model of the tumor cells. Second, a novel intelligent nonzero-sum games-based ADP is put forward to solve the optimization control problem by reducing the growth rate of tumor cells and minimizing chemotherapy drugs and immunotherapy drugs. Meanwhile, the convergence analysis and iterative ADP algorithm are specified to prove feasibility. Finally, simulation examples are listed to account for availability and effectiveness of the research methodology.

中文翻译：

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使用自适应动态规划的免疫系统非零和博弈的最优调节策略

本文研究了基于自适应动态规划（ADP）的免疫系统非零和博弈的最优控制策略问题。首先，主要目标是在肿瘤细胞和免疫细胞群之间近似纳什平衡，这是由肿瘤细胞数学生长模型引导的化疗药物和免疫剂控制的。其次，提出了一种新型的基于智能非零和博弈的 ADP，通过降低肿瘤细胞的生长速度和尽量减少化疗药物和免疫治疗药物来解决优化控制问题。同时，详细说明了收敛性分析和迭代ADP算法，证明了其可行性。最后，列出了模拟示例以说明研究方法的可用性和有效性。