Current Search: Garrett, Randy L. (x)
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Title
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G-LOG: A PROLOG SEMI-COMPILER FOR NON-PROCEDURAL SOFTWARE TOOLS.
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Creator
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Garrett, Randy L., Florida Atlantic University
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Abstract/Description
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G-LOG is a PROLOG semi-compiler written in the C programming language. G-LOG was designed to be a transportable, easily extensible non-procedural language which provides easy access to routines written in other programming languages. A primary use of G-LOG will be for the construction of a non-procedural executive for an expert system which calls existing routines to execute procedural functions. This versatility should enable industry investments in complex programs to be updated into a...
Show moreG-LOG is a PROLOG semi-compiler written in the C programming language. G-LOG was designed to be a transportable, easily extensible non-procedural language which provides easy access to routines written in other programming languages. A primary use of G-LOG will be for the construction of a non-procedural executive for an expert system which calls existing routines to execute procedural functions. This versatility should enable industry investments in complex programs to be updated into a customized expert system. The history and philosophy of PROLOG is sketched first, then the syntax required by G-LOG is presented. The implementation of G-LOG is discussed in detail. Novel aspects of G-LOG include semi-compilation of variables and user-written system primitives. Guidelines for the application programmer are given.
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Date Issued
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1984
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PURL
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http://purl.flvc.org/fcla/dt/14216
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Subject Headings
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Prolog (Computer program language), Computer software
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Format
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Document (PDF)
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Title
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A graphical approach to the traveling salesman problem.
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Creator
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Garrett, Randy L., Florida Atlantic University, Hoffman, Frederick, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
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Abstract/Description
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This report details an approach to solving the Traveling Salesman Problem (TSP) using learning automata and a unique geometric approach. Two-dimensional Euclidean TSPs are considered and the type of learning automata used are commonly called neural networks. A standard neural net algorithm called back propagation proved to be fairly good at learning the sample figures, but a newer substitute for back propagation, called counter propagation, performed extremely well. An important goal of this...
Show moreThis report details an approach to solving the Traveling Salesman Problem (TSP) using learning automata and a unique geometric approach. Two-dimensional Euclidean TSPs are considered and the type of learning automata used are commonly called neural networks. A standard neural net algorithm called back propagation proved to be fairly good at learning the sample figures, but a newer substitute for back propagation, called counter propagation, performed extremely well. An important goal of this research was to derive increased theoretical understanding of the TSP. This goal has been satisfied, especially with regard to instabilities in path length and the order of points traversed along the minimal path route. In addition, some applications to larger point problems are considered, and it is shown that configurations with isolated clusters of relatively closely spaced points relative to the convex hull apexes and the fixed points map quite well into the geometric figures presented here.
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Date Issued
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1989
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PURL
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http://purl.flvc.org/fcla/dt/11939
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Subject Headings
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Traveling-salesman problem
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Format
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Document (PDF)