#### **[Link to Gantt chart (login required)][1]** #### DARPA’s Next Generation Social Science (NGS2) program aims to develop new methods, tools, and techniques to answer research questions concerning complex social systems, which are difficult or impossible to address with current methods. When examined individually, each theory arising from research on social systems may seem straightforward and plausible. When reviewed collectively, however, it becomes apparent that theories are mutually incoherent and models are logically incompatible, giving rise to the so-called “incoherency problem” (Watts, 2017). Currently in the 2nd of 4 research cycles, we have prepared a series of Registered Reports which address two primary research questions about group innovation in competitive environments by introducing several new, generalizable methods and techniques to advance the state of the art in social systems research. Interdisciplinary teams including social scientists, cognitive scientists, computational biologists, data scientists, computer scientists, statisticians, and game theorists have worked for fifteen months to develop and demonstrate their capabilities and are now prepared to validate their methods on a complex problem of national importance. Briefly, these methods include an abductive loop framework to systematically decrease uncertainty, a sequential split-sample design using a Bayesian active learning algorithm, incorporation of artificial intelligence with programmed evolutionary behaviors, statistical models for comparing results across different data generating mechanisms, and an effect size prediction market to predict the contribution of various theories to the experimentally observed phenomena. [1]: https://www.teamgantt.com/gantt/schedule/?ids=728471#&ids=728471&user=&custom=&company=&hide_completed=false&date_filter=&color_filter=