Towards Understanding and Refining the General Program Synthesis Benchmark Suite with Genetic Programming
Towards Understanding and Refining the General Program Synthesis Benchmark Suite with Genetic Programming
复制标题
理解和完善遗传编程的通用程序综合基准套件
DOI：
10.1109/cec.2018.8477953
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. O’Neill
中科院分区：
文献类型：
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作者：
Stefan Forstenlechner;David Fagan;Miguel Nicolau;M. O’Neill
程序综合是一个复杂的问题域，许多社区通过不同的方法来解决。在过去的几年里，已经取得了很大的进展与遗传编程（GP）解决各种一般的程序综合问题，其中的基准套件已经推出。虽然遗传编程能够为包含在一般程序合成问题基准套件中的许多问题找到正确的解决方案，但在大多数情况下，每个问题的实际成功率很低。在本文中，我们分析了某些方面的基准套件和计算所需的努力，以解决其问题。GP表现不佳的问题的一个子集被确定。对这一子集进行分析，以找到提高类似问题成功率的措施。本文最后提出了改进程序综合问题性能的建议。
Program synthesis is a complex problem domain tackled by many communities via different methods. In the last few years, a lot of progress has been made with Genetic Programming (GP) on solving a variety of general program synthesis problems for which a benchmark suite has been introduced. While Genetic Programming is capable of finding correct solutions for many problems contained in a general program synthesis problems benchmark suite, the actual success rate per problem is low in most cases. In this paper, we analyse certain aspects of the benchmark suite and the computational effort required to solve its problems. A subset of problems on which GP performs poorly is identified. This subset is analysed to find measures to increase success rates for similar problems. The paper concludes with suggestions to refine performance on program synthesis problems.
DOI：
10.1007/978-3-662-44923-3
发表时间：
2014-09
期刊：
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影响因子：
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作者：
Gerson Zaverucha;V. S. Costa;A. Paes
通讯作者：
Gerson Zaverucha;V. S. Costa;A. Paes