The inference of concurrent systems using genetic programming

遗传编程是一种人工智能技术，它利用模拟达尔文的自然进化来进化计算机程序。本研究将遗传编程应用于并发程序的自动合成。这些程序采用过程代数的形式，这是用于简洁地表示并发计算的数学系统。使用进化来自动创建并发系统是一个有用的想法，因为并发程序本身对于编程和理解都是复杂的。该技术的一个应用是生物网络合成。研究人员最近发现，过程代数对于表示和模拟生物过程是实用的。利用遗传编程，这样的“生物网络”可以自动合成，以匹配从实验室获得的期望目标行为。这可能在未来用于分析复杂的生物现象。

Genetic programming is an artificial intelligence technology that uses a simulation of Darwinian natural evolution to evolve computer programs. This research applies genetic programming towards the automatic synthesis of concurrent programs. These programs take the form of process algebras, which are mathematical systems used to concisely represent concurrent computation. The use of evolution to automatically create concurrent systems is a useful idea, since concurrent programs are inherently complex to program and understand. An application of this technology is that of biological network synthesis. Researchers have recently discovered that process algebra are practical for representing and simulating biological processes. Using genetic programming, such "bionetworks" can be automatically synthesized, to match desired target behaviors obtained from the laboratory. This may be used in the future for analyzing complex biological phenomenon.