MOD: Co-Evolution of Innovative Products by Purposive Agents and the Growth of Technological Complexity

创新是经济的驱动力，往往伴随着技术的复杂性。创新自然可以被建模为由有目的的个人完成的各种经济产品的共同进化。本项目利用与生物进化有关的研究文献以及更传统的技术创新经济模型，以创建一个基于主体的计算模型，在该模型中，有目的的参与者(模拟为主体)发明新项目，新产品扩散到经济中，经济商品的数量和多样性随着时间的推移而增加，经济的技术复杂性与主体一起增长？福利。智力价值这类模型能够产生实际创新系统的许多风格化特征，例如永久变化、创造性破坏、不断提高人类生活水平以及复杂的相互关联的技术链。通过创建技术创新过程的高保真模型，可以更好地理解政策如何催化创新。现在是通过将最先进的计算机科学技术与当今社会科学中关于创新的已知知识相结合的方式，对创新模式进行跨学科研究的好时机。这个项目包括进化计算、社会网络分析和行为经济学的元素，有望成为研究科学政策的一种新方法。广泛的影响：创新影响现代生活的方方面面，更广泛的影响隐含在对科学发现和工业商业化过程的任何更好的理解中。具体地说，该项目向基础研究社区以外的各种受众展示了这项研究建立的各种模型。乔治梅森大学附近的杰出的托马斯·杰斐逊科技高中就是这样一项外展活动的所在地。在那里，计算机科学班的大四学生可以选择执行一个为期一年的项目，主题是他们自己选择的。他们越来越多地在社会科学中选择主题，并建立基于代理的模型来实现这些主题。这个项目的研究人员与那里的计算机科学教师合作，让他们的一些学生参与到与科学和技术政策相关的模型中。

Innovation is a driving force in the economy, and is often accompanied by technological complexity. Innovation can naturally be modeled as the co-evolution of a variety of economic goods accomplished by purposive individuals. This project draws on the research literature associated with biological evolution together with more conventional economic models of technological innovation in order to create an agent-based computational model in which purposive actors (simulated as agents) invent new projects, new products diffuse into the economy, the number and diversity of economic goods increases over time, and the technological complexity of the economy grows alongside the agents? welfare. Intellectual MeritThis class of models is capable of generating many of the stylized features of actual innovation systems, such as perpetual change, creative destruction, continuously increasing human living standards, and complex chains of inter-related technologies. By creating a high-fidelity model of the technological innovation process, a better understanding of how policy catalyzes innovation is developed. This is a fertile time to make cross-disciplinary approaches to models of innovation, by mixing state-of-the-art computer science techniques with what is known today about innovation within the social sciences. This project includes elements from evolutionary computation, social network analysis, and behavioral economics, and promises to be a new way to investigate the science of science policy.Broader Impacts: Innovation affects all aspects of modern life, and broader impacts are implicitly part of any improved understanding of scientific discovery and industrial commercialization processes. Specifically, the project exposes the kinds of models built by this research to a variety of audiences outside the basic research community. The outstanding Thomas Jefferson High School for Science and Technology, near George Mason University, is the location of one such outreach activity. There, seniors in computer science classes may elect to execute a year-long project on a topic of their choice. Increasingly, they choose topics in the social sciences and build agent-based models to realize them. The researchers on this project work with computer science teachers there to engage some of their students to work on models related to science and technology policy.