Garrett, Randy L.

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 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.

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 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.