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本文认为。信息科学可以看作是由控制论、信息论和一般系统论组成的统一的和具有统一能力的抽象科学,介于哲学和具体学科专业之间。它处于较高认识论层次上。虽不长于提出解决问题的具体办法,但有较大指导和方法论的意义。本文提出最小复杂性原理,认为任何系统向题的最小复杂性在性能指标固定时,可以分解和转移,但不能减少,如减少则必须拌随着性能指标的降低。并认为与性能最优化相对偶的最小复杂性提法是今后处理系统向题的一个有意义的方向。本文还提出广义时空互易原理,认为在任何系统向题中,都存在一对互补的广义时间和广义空间变量,它们的乘积总是大于或等于一个与性能指标有关的常数。广义时空之间的这种互易关系可为我们解决系统问题提供多种途径。
This paper argues that. Information science can be seen as a unified and unified abstraction composed of cybernetics, information theory and general system theory, between philosophy and specific disciplines. It is at a higher epistemological level. Although not longer than the specific solution to the problem, there is greater guidance and methodological significance. In this paper, the principle of minimum complexity is proposed. It is considered that the minimum complexity of any system problem can be decomposed and transferred when the performance index is fixed, but can not be reduced. For example, the reduction must be accompanied by the decrease of the performance index. And considers that the least complicated formulation that is comparable to performance optimization is a meaningful direction for handling system problems in the future. This paper also proposes the principle of generalized spatio-temporal reciprocity, and holds that there exists a pair of complementary generalized space and generalized space variables in any system problem, whose product is always greater than or equal to a constant related to performance index. This reciprocal relationship between generalized space-time provides many ways for us to solve system problems.