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确界
表示论之同一性说基底与维度组合聊拓扑时空区划与隶属判定
悟有无之恒定性说虚实与数字孪生聊循环递归仿生与复杂涌现
临界
加减律之取向性说测度与距离空间聊对称破缺逼近与因果语义
上下限之有界性说规模与尺度悖论聊意向生态仿真与意识自我
跨界
物智链之构造性说万联与边界超越聊解构析构同构与通道机制
特征值之传递性说转换与等价超类聊感知识别提取与滤波降噪
过界
周期律之规则性说运算与封闭环路聊张量积无穷势与全真度量
安全阈之运动性说状态与赋范变量聊演绎演生生息与系统控制
生演
脑科学之层次性说认知与智慧构造聊人机意识进化与思想延拓
看成败之可行性说超越与博弈进程聊自然而然了然与通道透析
不息
负反馈之互作性说响应与生成函数聊学习扩域纠错与自我革命
孕镜像之全息性说真实与模式模型聊完备理想全能与新界融通
In the context of intelligent and wise systems, people's intentional ecology will be more evident in the design and use of intelligent systems. Intelligent systems must not only meet people's basic needs but also align with their values and moral standards, thereby achieving harmonious coexistence between humans and intelligent systems. Through bionic simulation, we can draw inspiration from biological systems to design intelligent systems with functions such as autonomous learning, self-repair, and self-optimization. These systems can not only adapt to environmental changes but also improve their performance through continuous learning and optimization. In the context of intelligent and wise systems, intuitive judgment can be regarded as an important capability of intelligent systems. Intelligent systems can extract useful information from vast amounts of data through technologies such as deep learning and make rapid and accurate judgments based on this information. This capability is crucial for improving the response speed and decision-making efficiency of intelligent systems. Delving into the essence of a problem is key to efficiently solving it. We need to clarify the definition, scope, boundaries of the problem, as well as the goals and constraints for solving it. By deeply analyzing the essence of the problem, we can better understand its inherent laws and complexity, thereby formulating more scientific and reasonable solutions. In the research of intelligent and wise systems, rational approximation can be seen as an important solution strategy. By continuously optimizing algorithms and models, we can gradually approximate the optimal solution to the problem, thereby achieving more efficient and accurate intelligent decision-making. In the research of intelligent and wise systems, logical consistency is an important guarantee for ensuring the validity of arguments. We need to ensure that every step in the argumentation process is reasonable and well-founded, and that the steps are mutually supportive and coordinated. Complete unsolvable domain evolution refers to the possibility of encountering problems or areas that cannot be fully solved in the research of intelligent and wise systems. These unsolvable domains may arise due to the complexity, uncertainty of the problem, or information gaps. However, even within these unsolvable domains, we can still gradually approximate the optimal solution to the problem or find feasible solutions through continuous learning and evolution. This process of evolution is of great significance for advancing the development of intelligent and wise systems.
附记 海洋环境梯度与台风生成、强度和路径
梯度旋度下响应与适应 能量与因应信息流 中观生态动力 深度学习与数据挖掘 机器证明与人工智能 智能智慧化进程
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