人工智能领域广泛应用抽象概念，用于管理表示语言中不同细节层次，或在保持重要特征的同时切换层次。研究主要集中在问题解决、定理证明、知识表示（特别是空间和时间推理）以及机器学习等方面。在这些语境中，抽象被定义为形式化之间的映射，降低了所考虑任务的计算复杂度。从信息量角度分析抽象概念，可以识别任何表示变化中重构和抽象的区别与互补作用。抽象是人类和人工智能感知、知识表示、推理和学习的基础机制，是计算机编程、自然和人工智能视觉、复杂系统、人工智能和机器学习、艺术以及认知科学等多个领域的基本概念。

🤔**抽象是简化过程**: 在计算机科学中，抽象用于隐藏实现细节，从而将重点放在接口而不是实现上，例如，程序员使用库函数时，通常不需要知道该函数是如何实现的，只需要知道如何调用它以及它做什么。

💡**抽象用于管理不同细节层次**: 人工智能中，抽象用于管理表示语言中不同细节层次，或在保持重要特征的同时切换层次，例如，在解决问题、定理证明、知识表示等任务中，抽象可以降低计算复杂度。

💻**抽象应用广泛**: 抽象是计算机编程、自然和人工智能视觉、复杂系统、人工智能和机器学习、艺术以及认知科学等多个领域的基本概念，它为人类和人工智能的感知、知识表示、推理和学习提供了基础机制。

📚**抽象研究方向**: 抽象的研究主要集中在问题解决、定理证明、知识表示（特别是空间和时间推理）以及机器学习等方面，通过从信息量角度分析抽象，可以识别任何表示变化中重构和抽象的区别与互补作用。

In the most general sense, abstraction is the process of removing characteristics from something in order to reduce it to a set of essential characteristics. In computer science, abstraction is used to hide details of implementation in order to allow the focus to be on the interface rather than the implementation. For example, when a programmer uses a library function, they generally do not need to know how that function is implemented, only how to call it and what it does. This allows programmers to work at a higher level and makes code more reusable. Similarly, in object-oriented programming, abstraction is used to hide the implementation details of an object and instead provide a set of methods that can be used to manipulate the object. This allows objects to be treated as black boxes, which makes code more robust and easier to maintain.

Abstraction in artificial intelligence (AI)

Abstraction is a widely used concept in artificial intelligence to manage the use of different levels of detail in a representation language or the ability to switch between levels while preserving important characteristics. Its study has been mainly focused on problem-solving, theorem proving, knowledge representation (especially for spatial and temporal reasoning), and machine learning. In these contexts, abstraction is defined as a mapping between formalisms that reduces the computational complexity of the task being considered. By analyzing the concept of abstraction from an information quantity perspective, we can identify the differences and complementary roles of reformulation and abstraction in any representation change.

Abstraction is a critical mechanism that underlies human and artificial perception, knowledge representation, reasoning, and learning. It is a fundamental concept in various fields, including computer programming, natural and artificial vision, complex systems, artificial intelligence and machine learning, art, and cognitive sciences.

Books

Abstraction in Artificial Intelligence and Complex Systems By Saitta, Lorenza, Zucker, Jean-Daniel Buy on Amazon