SOLICITATION NOTICE
A -- Proactive Intelligence (PAINT) - PART 1 of 2
- Notice Date
- 10/24/2006
- Notice Type
- Solicitation Notice
- NAICS
- 541710
— Research and Development in the Physical, Engineering, and Life Sciences
- Contracting Office
- Department of the Air Force, Air Force Materiel Command, AFRL - Rome Research Site, AFRL/Information Directorate 26 Electronic Parkway, Rome, NY, 13441-4514
- ZIP Code
- 13441-4514
- Solicitation Number
- Reference-Number-BAA-07-01-IFKA-PART-1
- Description
- BAA-07-01-IFKA PART 1 OF 2 CFDA Number: 12.800 DATES: It is recommended that white papers be received by the following dates to maximize the possibility of award: FY 07 should be submitted by 4 Dec 06; FY 08 by 1 Oct 07; FY 09 by 1 Oct 08; FY10 by 1 Oct 09; and FY11 by 1 Oct 10. White papers will be accepted until 2 p.m. Eastern time on 1 May 2011, but it is less likely that funding will be available in each respective fiscal year after the dates cited. FORMAL PROPOSALS ARE NOT BEING REQUESTED AT THIS TIME. See Section IV of this announcement for further details. I. FUNDING OPPORTUNITY DESCRIPTION: The Air Force Research Laboratory (AFRL)/IF, in conjunction with the Intelligence Community's Disruptive Technology Office (DTO), is soliciting white papers for innovative, creative, and high-risk research to advance the state-of-the-art in technologies and methods for Proactive Intelligence (PAINT). Background The Intelligence Community has a central mission to help the nation avoid strategic national security surprise. Strategic surprises may come in the form of deliberate actions by adversaries of the United States, or they may emerge as unanticipated consequences brought about by the convergence or emergence of innocuous technological, economic, demographic, political, or natural forces. In each case, it falls to intelligence analysts to spot the indicators or informal signs of situations that may threaten the US in the ever-growing volume, variety and complexity of data; to organize the indicators and findings into a coherent picture; to support accurate predictions of future situations and their potential impacts; and to identify factors influencing the evolution of the situation. Technologies are needed which facilitate integration of diverse data into a coherent picture for analysis of future developments, and for collaboration among individuals and agencies. To address this need, the PAINT vision is for an integrated intelligence capability enabling policy-makers and operational users to better comprehend the present and to understand and more effectively shape the future. Thus, PAINT provides integrated intelligence that anticipates developments of strategic concern and identifies opportunities as well as vulnerabilities. The purpose of the BAA is to develop the methods and technologies that will demonstrate, implement, and evaluate the PAINT vision. Program Goals The program has four goals: 1) To develop predictive models of current or emergent situations that may threaten the US. These models should span the entire life-cycle of situations and should be inclusive of the environmental context. 2) To identify factors and strategies that may influence the evolution of these threats. 3) To develop methods for determining comprehensive indicators of these threats. 4) To use real world data and key indicators as feedback to adjust the models, their predictions, and potential influence strategies in goals 1-3. Technical Topic Areas for the PAINT Program To fulfill these goals, PAINT solicits white papers for research in four Topic Areas and in the interrelationships among them: 1. Models: The approach to model development will be assessed for creativity and innovation that allows: a) rapid implementation and modification (in days), b) a comprehensive ability to describe, explain, and support predictions of specified threatening situations, c) the integration of the models into a Virtual World/Dynamic Gaming Environment, and d) model validation. 2. Dynamic Gaming and Strategies: The proposed capability for a virtual world/dynamic gaming environment will be assessed for how well it can: a) rapidly predict a range of plausible future events and/or historical antecedents, and b) address a specified problem through the use of current data and key indicators. 3. Key Indicators: The credibility, efficiency, and focus of the proposed process for developing key indicators from low level data will be assessed for how well it: a) uses available data as well as steers collection of new data, and b) provides feedback for tuning models and simulations, and for evaluating predictions of real world events. 4. Architecture and Integration: The architecture needs to a) integrate the components developed in 1-3 above, b) enable the flexible and low-cost addition of new components, and c) support validation of the integrated system. Technical Overview This BAA proposes an overall challenge problem: How should the Government locate and discover terrorist networks; describe them in the context of the political, religious, social and economic networks that intersect with, influence, and are influenced by, the terrorist network; explain the structure and topology of the terrorist network; predict the formation, evolution, vulnerabilities, and dissolution of the network; and identify strategies to shape or influence the network through selective action? The expression integrated intelligence capability enabling the policy-maker and operational user to better comprehend and to more effectively shape the future incorporates several important ideas: (1) the development of models and simulations to describe, explain, and predict situations and to serve as modular building blocks for a dynamic game/virtual world platform; (2) a dynamic game/virtual world platform where collaborative integration of data and analyses occurs across individuals, activities and agencies; (3) the use of a virtual world to identify critical factors and vulnerabilities and to develop influence strategies that affect future developments; (4) the application of current data and key indicators to evaluate the coherence and validity of the integrated picture provided by the virtual world; and (5) the capability to use this virtual world to identify "missing elements" for guiding collection. As additional detail and information are incorporated, the parameters of the virtual world and near-term predictions can be evaluated against new data to provide a rigorous, ongoing evaluation; to update the models; and to adjust the influence strategies. The PAINT program is focused on technologies for the rapid development of the virtual world/gaming environment and for the rapid generation and evaluation of predictions relative to the available data. A related program, Advanced Research in Interactive Visualization for Analysis (ARIVA), will be concentrating on the user interface front end by developing new technologies for multi-modal interfaces serving multiple domains of expertise. The PAINT program intends to leverage emerging technologies to enable the rapid creation of predictive and analytic models and simulations. These models and simulations provide modular building blocks for a dynamic game/virtual world where the evolution of a specific network(s) can be analyzed. Then, critical factors and vulnerabilities in alternative futures of that network can be identified to enable development of viable shaping strategies by policy-makers and operators. The knowledge of networks provides a set of constraints or boundaries within which gaming and simulation (a common environment) can be used to extend the known into the future. This common environment is used to integrate data, to develop predictions, and to identify critical factors and vulnerabilities which can be tested against data. Dynamic gaming, whether competitive or cooperative, serves to introduce human judgment to account for ambiguous or poorly understood factors and to evaluate the coherence of the virtual world. The testing process serves to validate both the predictive models and the shaping strategies. In summary, the dynamic game/virtual world provides the basis for making predictions about the future, for developing influence strategies to affect the future, and for driving data collection to evaluate the models, predictions, and strategies. Important Technical Ideas The Government encourages offerors to identify their own important technical issues beyond the following list. However, white papers should consider the following: 1) Integration of modeling & simulation with the emerging science of network analysis applied to distributed human groups/activities, 2) Architectures for rapid development of simulations and models that can explain, describe, and predict situations, 3) Development of problem-focused collaborative virtual world/dynamic game environments that can incorporate component models and simulations as well as real world data to enable the rapid exploration of strategies, 4) Manipulation of the virtual worlds in parallel to the real world to identify critical factors, vulnerabilities and shaping strategies, 5) Use of data filtering, data analysis, and other technologies to identify problem-specific, comprehensive collections of key indicators, 6) Controlled application of assessment techniques to validate the outputs of the models and games against historical antecedent and actual events, 7) Metrics and methods that tune the virtual world (and component models and simulations) against problem-specific data and feedback from near-term predictions, 8) Systems integration issues and/or architecture concepts. Example Variations of the Challenge Problem The following topics represent possible expansions of the above challenge problem. Offerors may choose to use these or others problems to explain their approach. 1. Nuclear Non-proliferation. Terrorist networks depend on the threat of destruction and the resources to carry out those threats. The possession of nuclear and biochemical weapon capability by unstable countries, by countries hostile to the US or by countries that are sympathetic to terrorist causes are, of course, major threats. The technology to develop a weapon is available easily but obtaining the supplies to develop them or buying the weapons is difficult. The problem is complicated because the US may not know whether a country: has supplies, has the capability to produce weapons, or has the presence of terrorist insiders or links to terrorist networks. A major challenge is to describe the network of activities characteristic of nuclear energy/weapon development. We must describe these programs in the context of the local religious, social and political networks and the multi-national political and economic situation; explain the structure of the research infrastructure for nuclear energy development using multiple indicators that distinguish offensive programs from peaceful ones; predict the evolution from what may be legal activities to weapons production; and recommend how to steer activities in peaceful directions. Networks of indicators must be identified and interrelated to represent different stages of offensive capabilities. This result should enable rapid creation of strategies for shaping development to blunt nuclear proliferation. 2. Denied Area Ethnography. The challenge problem speaks of a terrorist network coexisting within and across the socio-political, economic and religious contexts of various nations. The coexistence is at times symbiotic and on occasion parasitic. Understanding the nature of these relationships is rooted in knowing how an organization or a country functions and the principles that guide that functionality. Denied area ethnography is the ability to use multiple sources (news media, references, web info, info in their language, academics who have studied the area, businesses that deal with the local area and speak the language) to probe countries or regions where the US has no presence and must extract information from foreign sources. The information must allow us to build a data-based conceptual model of that culture in terms of where people look for security; what constitutes legitimacy; and who actually controls government and commerce. In this context, developing models of the cultural networks, deriving key cultural indicators, and creating a virtual world or dynamic game of an organization or culture provides both a method of integration and a structure for evaluating the coherence of information.
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