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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.
The program will make the computational models available, accessible, and understandable to operators, providing them with an “insider” view to support operational decision making. The resulting capability will be specific enough to anticipate system-level effects in response to events that are generalizable across regions and populations, adaptive as societies change over time, and self-sustaining for maintainability and persistence.
o TA1/ TA2 Abstract Due Date: February 28, 2020, 4:00 p.m
o TA1/TA2 Full Proposal Due Date: April 23, 2020, 4:00 p.m
o CE Full Proposal Due Date: TBD
o BAA closing date: August 17, 2020
Areas of Interest
Habitus consists of two Technical Areas (TAs) and a Comparative Evaluation (CE) team in support of a government Testing and Evaluation (T&E) team.
- TA1: Model Development : TA1 will develop scalable and generalizable knowledge elicitation methods to semi-automatically and rapidly derive computational model factors and system level relationships (the system model).
- TA2: Engagement Mechanism : TA2 will create a self-sustaining capability that continually provides information necessary to build and update TA1’s computational models by providing value to the local users. The solution can be based on either passive observation or active engagement.
- CE: Comparative Evaluation: The Comparative Evaluation (CE) team will generate parallel predictions to those specified by TA1/TA2 using current methods in order to generate a question-for-question comparative data set that the government T&E team will use to evaluate performance.
This BAA comprises two proposal submission periods. The first submission period is for TAs 1 and 2. Because the engagement mechanisms will depend heavily on model development strategies, and vice versa, all proposals submitted during the first submission period must address both TA1 and TA2. The CE component is also being solicited under this BAA; however, additional technical detail regarding CE will be published in a subsequent BAA amendment. The amendment will also include requirements for submitting a proposal and due dates. The description of CE that follows is for informational purposes only in order to facilitate proposing to TA1/TA2. In order to ensure the impartiality of the evaluation of the TA1 and 2 technology, proposers selected for negotiation of an award for TA1/TA2 will not be eligible to propose to the CE BAA Amendment.
While proposers may submit proposals for both Technical Area 1 and 2 and the CE portion, TA1/TA2 awardees cannot be selected for the CE portion as a prime proposer, subawardee, or in any other capacity from an organizational to individual level. This is to avoid conflicts of interest between the Technical Areas and the CE portion and to ensure objective test and evaluation results. The decision as to which proposal(s) to consider for award is at the discretion of the Government.