Visiting Fellowship: Bringing contemporary biology into Evolutionary Computation: Plasticity, hierarchy, and genetic re-use

进化计算是计算机科学的一个分支，使用达尔文进化论和遗传学的思想来设计系统和算法。进化算法从一个问题的原始随机试探性解决方案开始，一代又一代地使用基因突变和重组以及适者生存的原则来改进它们。这最终会导致为手头的问题创造出高度合适的新颖解决方案。进化计算提供了数十个与人类竞争的显著结果。然而，就我们目前能够发展的各种解决方案的大小和复杂性而言，存在明显的限制。主要问题有：有限的模块化（模块化是指用较小的、半独立的系统构建大型系统的能力）；*有限的可扩展性（可扩展性指的是运行问题解决程序的计算工作量随着问题规模的增加而增加的速度有多快），*缺乏可塑性（可塑性指的是解决方案根据外部条件和事件改变其行为的能力）这个项目将用一种全新的方法解决进化计算中的所有三个重要问题，其灵感来自于已经解决这些问题的生物学。

Evolutionary computation is a branch of computer science using ideas from Darwinian evolution and genetics to design systems and algorithms. Starting from a primordial ooze of random tentative solutions to a problem, generation after generation, evolutionary algorithms refine them using genetic mutations and recombinations and the principle of survival of the fittest. This ultimately leads to the creation of highly fit novel solutions to the problem at hand. Evolutionary computation has provided tens of remarkable human-competitive results. However, there are clear limits in terms of the size and complexity of the kinds of solutions we are able to currently evolve. The main problems are: * limited modularity (modularity is the ability to build large systems out of smaller, semi-independent ones), * limited scalability (scalability refers to how rapidly the computational effort of running a problem-solver increases with the size of the problems),* lack of plasticity (plasticity refers to the ability for a solution to change its behaviour in response to external conditions and events)This project will tackle all three of these significant problems in evolutionary computation with a radically new approach, inspired by biology that has already solved these problems.