AI 中文总结
本文针对受Gronwall型约束的线性动力学多智能体追逃问题，构建追捕者许可策略并推导拦截保证的充分条件，通过数值示例验证策略有效性与分析条件。
AI 中文摘要
本文研究多智能体追逃问题，其中一组追捕者需在固定操作时间范围内拦截一个或多个逃避者。追捕者与逃避者的运动由一阶线性微分方程描述，智能体可用的控制输入受Gronwall型约束限制。当至少一个追捕者在规定时长内的有限时间到达每个逃避者的位置时，追逃判定为成功。在该框架内，我们为追捕者构建了许可策略，并推导了充分条件，确保即使存在逃避者的反制行动，拦截仍能得到保证。为支撑理论结果，我们给出了数值示例，以证明所提策略的有效性并确认成功追逃的分析条件。
英文摘要
This paper investigates a multi-agent pursuit problem in which a group of pursuers seeks to intercept one or more evaders within a fixed operational time horizon. The motion of both pursuers and evaders is described by first-order linear differential equations, and the control inputs available to the agents are subject to Gronwall-type constraints. Pursuit is considered successful when at least one pursuer reaches the position of each evader at a finite time within the prescribed duration. Within this framework, we construct permissible strategies for the pursuers and derive sufficient conditions under which interception is guaranteed despite the evaders' counteractions. To support the theoretical results, we present numerical examples that demonstrate the effectiveness of the proposed strategies and confirm the analytical conditions for successful pursuit.
