the complexity side of things is harder to explain. you can approach this theoretically, practically, or a mix of both. the theoretical approach is to look at the worst-case time complexity of each algorithm, and the practical approach is to look at how they perform on real-world inputs and benchmarks. let’s explore a bit of both.
首先，智能体应具备强大的目标理解和规划能力来体现智能的自主性。理想状态下，人类只需给出抽象目标，智能体便能理解目标、拆解任务、规划行动，并在尽量少的人工干预下完成执行闭环。就像影《星际穿越》中的机器TARS，在紧急情况下能够根据"拯救宇航员"这一目标，自主判断局势、制定和调整行动策略，甚至做出牺牲自己数据的决定来完成使命。这要求机器智能有深度“理解/思考”能力（推理、规划、决策），能够敏锐地决策，能够基于执行结果与环境反馈动态调整任务规划，而不是僵化地执行既定路径。
。业内人士推荐WPS下载最新地址作为进阶阅读
The full source code is available on GitHub: github.com/NickTikhonov/shuo
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It's also possible to deadlock this version of foo if we pause the thread