Every scientific or intellectual movement rests on central premises and assumptions that shape its philosophy. The purpose of this study is to review a brief account of the main philosophical bases of grey systems theory (GST) and the paradigm governing its principles. So, the recent studies on the philosophical foundations of GST have been reviewed and tried to pay attention to some key ambiguities in the previous studies and give more and clearer explanations in this paper. Also, this paper tries to fill the gap among the previous studies and to provide a purposeful connection between them by expressing two key concepts: complete information and imbalance knowledge. Primarily, the study addresses the theoretical foundations of uncertainty and the concept of greyness. Next, it focuses on the notion of “complete information” and challenges to it. Then, it reviews such processes as perception, cognition, and understanding, as well as their dynamic nature. It explains how knowledge is produced through understanding and interpreting information/data and the dynamics governing the whole process. Also, the study describes any dataset, no matter how large it may be, will remain incomplete, imperfect, and grey, so humans only rely on incomplete datasets to interpret the world. As such, information and knowledge are always grey and uncertain because they are basically contingent on subjective understandings and interpretations and imperfect inputs and data. Finally, as a key development, this study also demonstrates that human grey knowledge remains imbalanced across different disciplines and spheres. In the end, a brief overview of the philosophical paradigm of GST is also provided. GST is depicted as an anti-realistic, anti-positivistic, and non-deterministic approach, which is inherently pluralistic and ideographic. According to GST principles, dynamicity and change are essential parts of human narratives of the world and systems, and human knowledge is constantly reproduced through collecting new information. As a result, knowledge, theories, narratives, and scientific laws dynamically change. Given this premise, one could argue that GST is considerably compatible with the postulates of post-modern thinking.

每一项科学或知识运动都建立在塑造其哲学的中心前提和假设之上。本研究的目的是回顾灰色系统理论 (GST) 的主要哲学基础及其原则的范式的简要说明。因此，本文对近期关于 GST 哲学基础的研究进行了回顾，并试图关注前人研究中的一些关键歧义，并在本文中给出更多、更清晰的解释。此外，本文试图填补以往研究之间的空白，并通过表达两个关键概念：完整信息和不平衡知识，在它们之间提供有目的的联系。首先，该研究解决了不确定性和灰色概念的理论基础。接下来，重点关注“完整信息”的概念及其面临的挑战。然后，它回顾了感知、认知和理解等过程，以及它们的动态特性。它解释了如何通过理解和解释信息/数据以及控制整个过程的动态来产生知识。此外，该研究描述了任何数据集，无论它有多大，都将保持不完整、不完美和灰色，因此人类只能依靠不完整的数据集来解释世界。因此，信息和知识总是灰色和不确定的，因为它们基本上取决于主观理解和解释以及不完善的输入和数据。最后，作为一个关键的发展，这项研究还表明人类灰色知识在不同学科和领域之间仍然不平衡。最后，还简要概述了 GST 的哲学范式。GST 被描述为一种反现实主义、反实证主义和非确定性的方法，它本质上是多元的和表意的。根据 GST 原则，动态和变化是人类对世界和系统的叙述的重要组成部分，人类知识通过收集新信息不断地再现。因此，知识、理论、叙述和科学规律会动态变化。鉴于这一前提，有人可能会争辩说 GST 与后现代思维的假设相当相容。人类的知识通过收集新的信息不断地被复制。因此，知识、理论、叙述和科学规律会动态变化。鉴于这一前提，有人可能会争辩说 GST 与后现代思维的假设相当相容。人类的知识通过收集新的信息不断地被复制。因此，知识、理论、叙述和科学规律会动态变化。鉴于这一前提，有人可能会争辩说 GST 与后现代思维的假设相当相容。