The Mathematics of Multi-Agent Systems | MIT HSSP 2022
Description: Hi, I’m Sihao! I work in the intersection of comparative politics and complexity science. I’m currently studying at Schwarzman College in Tsinghua.
In social science, formal and quantitative models, such as ones describing economic growth and collective action, are used to formulate mechanistic explanations, provide predictions, and uncover questions about observed phenomena. Here, we demonstrate the use of a machine learning system to aid the discovery of symbolic models that capture nonlinear and dynamical relationships in social science datasets. By extending neuro-symbolic methods to find compact functions and differential equations in noisy and lo
Racial disparities in elite education received widespread attention in the wake of the 2020 Black Lives Matter (BLM) protests. Universities expressed their commitment to diversity, but policies aimed at rectifying historic disadvantages were met with numerous challenges. Notably, commentators have expressed concerns that these efforts would disadvantage academically successful white and Asian students. In this profile, we assess whether BLM protests were followed by an increase in the representation of Blac
The triumph of the natural sciences has inspired many attempts to transfer its methods to social inquiry. Although most have fallen short, there has been a handful of notable successes like empiricism and statistical theory. Complexity science is a new contender in this line of epistemologies, claiming to bring a new anti-reductionist framework for reasoning about social and political systems. There is, however, no lack of criticism over its lack of rigor and substantive novelty. Being a relatively new fiel
The Mathematics of Multi-Agent Systems | MIT HSSP 2022