Nature-inspired methods for hardware and software system design and information processing

我的研究探讨了知识工程，数学和自然启发的计算系统设计和分析的使用。它的基本假设是，大多数系统设计，建模和分析问题可以表示为分类或优化问题，其中存在自然等价物并在进化过程中得到解决，或者可以使用启发式搜索和/或数据挖掘开发创新的搜索算法。在这样做的时候，我寻求替代方法，现有的正式技术时，他们是不适用的或太慢。

My research investigates the use of knowledge engineering, heuristics and nature-inspired computation for system design and analysis. Its basic postulate is that most system design, modeling, and analysis problems can be represented as classification or optimization problems for which a natural equivalent exist and have been solved over the course of evolution, or for which innovative search algorithms can be developed using heuristic search and/or data mining. In doing so, I seek alternative approaches to existing formal techniques when they are inapplicable or too slow.