Work in automatic programming focusses on the problem of how to make the computer more accessible to the non-programmer. It involves both the design of interfaces and the development of algorithms to support those int...
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automatic programming, the automatic generation of a computer program given a high-level statement of the program's desired behaviour, is a stated objective of the field of genetic programming. As the general solu...
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automatic programming, the automatic generation of a computer program given a high-level statement of the program's desired behaviour, is a stated objective of the field of genetic programming. As the general solution to a computational problem is to write a computer program, and given that genetic programming can automatically generate a computer program, researchers in the field of genetic programming refer to its ability to automatically solve problems. Genetic programming has also been described as an "invention machine" that is capable of generating human-competitive solutions. We argue that the majority of success and focus of our field has not actually been as a result of automatic programming. We set out to challenge the genetic programming community to refocus our research towards the objective of automatic programming, and to do so in a manner that embraces a wider perspective encompassing the related fields of, for example, artificial intelligence, machine learning, analytics, optimisation and software engineering.
The integration of differential equations by recurrent power series is a classical method in ODE. This method is valid on very long spans of integration and unusually large step-sizes. However, this method is rarely u...
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The integration of differential equations by recurrent power series is a classical method in ODE. This method is valid on very long spans of integration and unusually large step-sizes. However, this method is rarely used, mainly since each problem requires a specific formulation. In this paper, we take advantage of the facilities of the modern general purpose algebraic manipulators to elaborate a general program that provides as output the Fortran code with the recurrent formulas needed for integrating any first order differential system. We present two applications, the Henon-Heiles problem, and the van der Pol's oscillator. For the last one, we make numerical comparisons between the recurrent power series method and a well tested Runge-Kutta one. (C) 1999 IMACS/Elsevier Science B.V. All rights reserved.
The authors consider five common myths about automatic programming and expose the fallacies on which they rest. They attempt to provide an accurate picture of these systems in terms of what the user sees, how the syst...
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The authors consider five common myths about automatic programming and expose the fallacies on which they rest. They attempt to provide an accurate picture of these systems in terms of what the user sees, how the system works, and what the system knows. They describe commercially available systems and discuss what is on the horizon
This paper describes a method for automatically generating software for a stored program telephone switching office. The system allows users to quickly specify the operation of the switching office using a formal desc...
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This paper describes a method for automatically generating software for a stored program telephone switching office. The system allows users to quickly specify the operation of the switching office using a formal description language. The description language is a set of situation, stimulus, and effect triples which collectively specify the behavior of the phones the switching office controls. The description is automatically compiled into programs which effect the desired behavior. There are two major advantages: 1) nonprogrammers can implement complex features and 2) modifications which require changes throughout the code running the system can be expressed in a single part of the description language.
Genetic programming ( GP) is an evolutionary algorithm which explores a program space rather than a solution space which is typical of other evolutionary algorithms such as genetic algorithms. GP finds solutions to pr...
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ISBN:
(纸本)9781479932306
Genetic programming ( GP) is an evolutionary algorithm which explores a program space rather than a solution space which is typical of other evolutionary algorithms such as genetic algorithms. GP finds solutions to problems by evolving a program, which when implemented will produce a solution. This paper investigates the use of genetic programming for automatic programming. The paper focuses on the procedural/imperative programming paradigm. More specifically the evolution of programs using memory, conditional and iterative programming constructs is investigated. An internal representation language is defined in which to evolve programs. The generational GP algorithm was implemented using the grow method to create the initial population, tournament selection to choose parents and reproduction, crossover and mutation for regeneration purposes. The paper also presents a form of incremental learning which facilitates modularization. The GP approach to automatic programming was tested on ten programming problems that are usually presented to novice programmers in a first year procedural programming course of an undergraduate degree in Computer Science. The GP approach evolved solutions for all ten problems, with incremental learning needed in two instances to produce a solution.
Finite State Linear Programs (FSLP) are introduced to model simple data processing applications. Essentially these are finite automata with the added capability of performing linear operations on a set of registers an...
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Finite State Linear Programs (FSLP) are introduced to model simple data processing applications. Essentially these are finite automata with the added capability of performing linear operations on a set of registers and the input. Algorithmic constructions are given to test equivalence of FSLP programs, and to minimize the number of states and registers. Linear algebraic methods are used for the register minimization procedure (and its correctness proof).
Binary image analysis problems can be solved by set operators implemented as programs for a binary morphological machine (BMM). This is a very general and powerful approach to solve this type of problem. However, the ...
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ISBN:
(纸本)0819419273
Binary image analysis problems can be solved by set operators implemented as programs for a binary morphological machine (BMM). This is a very general and powerful approach to solve this type of problem. However, the design of these programs is not a task manageable by nonexperts on mathematical morphology. In order to overcome this difficulty we have worked on tools that help users describe their goals at higher levels of abstraction and to translate them into BMM programs. Some of these tools are based on the representation of the goals of the user as a collection of input-output pairs of images and the estimation of the target operator from these data. PAC learning is a well suited methodology for this task, since in this theory 'concepts' are represented as Boolean functions that are equivalent to set operators. In order to apply this technique in practice we must have efficient learning algorithms. In this paper we introduce two PAC learning algorithms, both are based on the minimal representation of Boolean functions, which has a straightforward translation to the canonical decomposition of set operators. The first algorithm is based on the classical Quine-McCluskey algorithm for the simplification of Boolean functions, and the second one is based on a new idea for the construction of Boolean functions: the incremental splitting of intervals. We also present a comparative complexity analysis of the two algorithms. Finally, we give some application examples.
In modern manufacturing, it is urgent to require integrating manufacturing and inspection because manual inspection and off-line inspection severely restricts the development of inspecting automation. In the paper, au...
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ISBN:
(纸本)9780878492053
In modern manufacturing, it is urgent to require integrating manufacturing and inspection because manual inspection and off-line inspection severely restricts the development of inspecting automation. In the paper, automatic programming system based on solid driven technology for machining center on-line inspection has been developed by secondary development kit object ARX of CAD. Inspection feature datum and information were gotten by ARX tool in CAD stage, and then inspecting program can be automatically made up through inspecting process planning. On-line inspection automatic programming system based on solid driven technology has been applied in SSK-U6035 machining center. The application result shows that the programming system is simple and effective, which has realized integration of manufacturing and inspection more efficiently, increased precision, production efficiency and reduced the rate of rejection and tool damage.
Currently, manual inspection and off-line inspection play an important role in the inspection methods of machining process, which severely restricts the development of inspecting automation. In the paper, automatic pr...
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ISBN:
(纸本)9780878492268
Currently, manual inspection and off-line inspection play an important role in the inspection methods of machining process, which severely restricts the development of inspecting automation. In the paper, automatic programming system for machining center on-line inspection was developed by secondary development kit object ARX of AutoCAD. Inspecting datum was obtained, inspecting process planning was laid up and inspecting program was made automatically. The inspection can be applied to automatic workpiece setting up, on-line inspection of workpiece, data processing, quality analysis and compensation of machined workpiece errors, which led to increase precision, production efficiency and quality and reduced the rate of rejection and tool damage.
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