自我改进软件系统中的代码合成

Roberto Rodrigues Filho, A. Wild, Barry Porter
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引用次数: 2

摘要

这个扩展的抽象旨在引发关于代码合成及其在创建下一代自我改进软件系统中的重要性的广泛讨论。作为讨论的起点,提出了一个机器对机器的自改进框架。该框架旨在通过集成两个模块来提高系统的性能:i)自完善在线模块和ii)代码合成器离线模块。在线模块在运行时处理系统的输入时,学习如何从可用的软件组件和用户定义的高级目标中最好地组合系统。离线代码合成器根据感知到的系统输入、执行环境和在线模块提供的系统目标生成新的组件。代码合成器为在线模块与系统集成提供了更好的组件选择,以提高其性能。这篇摘要描述了这个框架,重点是它的主要挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Code Synthesis in Self-Improving Software Systems
This extended abstract aims at provoking a wide discussion around code synthesis and its importance in creating the next generation of self-improving software systems. As a starting point for the discussion, a machine-to-machine self-improving framework is presented. The framework aims at improving system's performance by integrating two modules: i) a self-improving online module, and ii) a code synthesiser offline module. The online module learns, at runtime, as it handles the system's inputs, how to best compose the system from a pallet of available software components and a user-defined high level goal. The offline code synthesiser generates new components based on the perceived system's input, executing environment and the system's goal provided by the online module. The code synthesiser then provides better component options for the online module to integrate with the system to improve its performance. This abstract describes the framework, focusing on its main challenges.
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