Meta-programming in logic programming by Harvey Abramson, M H. Rogers
By Harvey Abramson, M H. Rogers
Meta-programs, which deal with different machine courses as info, contain compilers, editors, simulators, debuggers, and application transformers. end result of the huge ranging functions, meta-programming has develop into a subject matter of substantial sensible and theoretical curiosity. This publication presents the 1st accomplished view of themes within the concept and alertness of meta-programming, protecting difficulties of illustration and of soundness and correctness of interpreters, research and assessment of meta-logic courses, and purposes to stylish knowledge-based systems.Harvey Abramson is Reader in computing device technological know-how on the college of Bristol, England; M. H. Rogers is Professor of machine technology, additionally on the college of Bristol. Meta-Programming in good judgment Programming is within the sequence good judgment Programming learn studies and Notes, edited via Ehud Shapiro.
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In the next subsection we present several examples of utilization of the performance measures. We will highlight how wrong selections of metrics aﬀect to the achieved conclusions. 1 Example 1: On the Absence of Information We begin our test showing the results of a SA with diﬀerent number of processors to solve an instance of MAXSAT. 2. The values showed are the number of executions that found the optimal value (% hit column), the ﬁtness of the best solution (best column), the average ﬁtness (avg column), the number of evaluations (# evals column) and the running time (time column).
This class of instances has the advantage of being freely available. Specially, academic instances must be analyzed in the existing literature to not reinvent the wheel, and to avoid using straightforward benchmarks . Standard Instances In this class are included the instances, benchmarks, and problem instance generators that, due to their wide use in experimentation, became standard in the specialized literature. For example, Reinelt  oﬀers the TSPLIB, a travelling salesman problem test instances, Demirkol et al.
At the beginning of each iteration, all the processors send the individuals of their ﬁrst/last column/row to their neighbor islands (see Fig. 6). After receiving the individuals from the neighbors, a sequential cGA is executed in each subpopulation. The remaining of the algorithms has a canonical implementation and no especial issues are used. For testing the parallel algorithms we have used the well-known MAXSAT problem. The next subsection brieﬂy describes the MAXSAT problem and then we discuss the results.