This Broad Agency Announcement (BAA) constitutes a public notice of a competitive funding opportunity as described in Federal Acquisition Regulation (FAR) 6.102(d)(2) and 35.016 as well as 2 C.F.R. § 200.203. Any resultant negotiations and/or awards will follow all laws and regulations applicable to the specific award instrument(s) available under this BAA, e.g., FAR 15.4 for procurement contracts.

The Defense Sciences Office (DSO) at the Defense Advanced Research Projects Agency
(DARPA) is soliciting innovative research proposals to create self-sustaining, adaptive,
generalizable, and scalable methods for generating causal system models based on local
knowledge to aid operational decision making. Understanding how to work with and influence local systems to support stability operations is critical for operational decision making and is most challenging in undergoverned regions in which the systems themselves are often in flux or illegible. Establishing stability in such regions requires we facilitate actions that are in line with local views, yet our current means for understanding local systems such as the political, socioeconomic, and/or those related to health and infrastructure are limited.

Humans develop causal cognitive representations – or cognitive models – of systems of which they are a part. These models include factors (or variables), relationships among factors, and contexts that affect both. The knowledge behind these models is often hyper-localized, changing dramatically with regional and/or population dependent interactions of factors such as terrain, industries, population density (urban, rural), shared history, formal and informal power structures, religion, and ethnicity. These cognitive models, though often implicit, allow one to estimate which factors are most important for a given outcome and how those factors interact to anticipate future outcomes based on history, current events, and trends.