Multi-objective grammar-guided genetic programming for bio-network modelling and evolutionary design

这项研究使用人工智能算法来自动构建生物模拟，并解决图形和设计中的问题。遗传编程是一种人工智能技术，它使用达尔文进化的模拟来创建计算机程序。这项研究将改进遗传编程的一些技术方面，以提高其解决复杂问题的有效性，这些问题对人类来说往往非常具有挑战性。例如，将衍生出表示解决问题的编程语言的新方法。评估问题的潜在解决方案的改进也将被发明。 将研究的遗传编程的一个应用领域是生物网络的自动构建。例如，给定一些表示蛋白质数量随时间变化的实验室数据，目标是让遗传编程自动使用这些数据来构建一个模型，解释这些数据如何在实验室中产生。这是一项具有挑战性的任务，因为这样的实验室数据通常非常复杂和嘈杂，并且难以分析。本研究的一个目标是发现分析这些数据的改进方法。此外，遗传编程将使用新的建模语言，以更有效地构建模型。在进化设计中的应用也将进行研究。在这些应用中，遗传编程可以用于创建绘画艺术，3D模型和结构，以及美术中的其他应用。这些问题与生物建模有许多共同的特征。例如，它们通常很难评估，并且它们可以受益于遗传编程系统中改进的编程语言表示。进化设计领域在我的学生中非常受欢迎，许多人已经进入研究生院在该领域工作。

This research uses artificial intelligence algorithms to automatically construct biological simulations, and solve problems in graphics and design. Genetic programming is an artificial intelligence technology that uses a simulation of Darwinian evolution to create computer programs. The research will improve some of the technical aspects of genetic programming, to improve its effectiveness at solving complex problems that are often very challenging for human beings to accomplish. For example, new ways of representing problem-solving programming languages will be derived. Improvements to evaluating potential solutions to problems will also be invented. One application area of genetic programming that will be studied is the automatic construction of biological networks.For example, given some laboratory data denoting the changing quantities of proteins over time, the goal is to have genetic programming automatically use this data to construct a model that explains how this data arises in the lab. This is a challenging task because such laboratory data is usually very complex and noisy, and difficult to analyze. A goal of this research is to discover improved means for analyzing such data. In addition, new modeling languages will be used by genetic programming, to more effectively construct the models. Applications in evolutionary design will also be investigated. These are applications in which genetic programming can be used to create painterly art, 3D models and structures, and other applications in the fine arts. Such problems share many characteristics of biological modeling. For example, they often are complicated to evaluate, and they can benefit with improved programming language representations within the genetic programming system. The field of evolutionary design has been very popular with my students, and many have proceeded to graduate school to work in the area.