Constraint Algebra-A Supervisory Programming Technique and a Cognitive Process

G. Friedman
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引用次数: 2

Abstract

Mathematical models of complex physical or bionic systems involve many simultaneous nonlinear equations. These groups of relationships are difficult to manipulate and even simulalation on a computer is unwieldy because most computational paths are multidirectional and are either over-or under-constrained. The foundation and purposes for an algebra of contraints are outlined in this paper. A typical application of constraint algebra would be as a supervisory routine for a digital program that operates on the topological properties of the set of the equations and determines the allowable computational paths. At the conclusion of these logical operations, which are performed with the aid of a constraint matrix, normal programming can be employed for the quantitative operations on the allowable paths. Thus, one more rational function in the man/computer relationship-that of the generation of perfectly constrained relationships-can now be taken over by the computer. The inclusion of a theorem from thermodynamics allows quite a different application: new variables may be deduced from the constraints which, together with their corresponding equations, simplify the model. This ability to synthesize new concepts (variables) and relationships (equations) which tend to simplify models can be considered as an analog for the cognitive process of abstraction.
约束代数——监督规划技术与认知过程
复杂物理或仿生系统的数学模型涉及许多联立非线性方程。这些关系组很难操作,甚至在计算机上进行模拟也很笨拙,因为大多数计算路径是多向的,要么是过度约束,要么是欠约束。本文概述了约束代数的基础和目的。约束代数的一个典型应用是作为一个数字程序的监督程序,该程序对方程集的拓扑特性进行操作,并确定允许的计算路径。这些逻辑运算是借助于约束矩阵来完成的,在这些逻辑运算的结论下,就可以利用常规规划对允许路径进行定量运算。因此,在人与计算机的关系中,一个更合理的功能——生成完全约束的关系——现在可以由计算机来接管。热力学定理的包含允许一个完全不同的应用:新的变量可以从约束中推导出来,连同它们相应的方程,简化了模型。这种综合新概念(变量)和关系(方程)的能力往往会简化模型,可以被视为抽象认知过程的类比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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