APPLIED INFORMATION SCIENCES FOR DECISION MAKING
Abstract
The goal of this activity is to support FORCEnet by developing enablers for decision making and mission execution, to achieve battlespace superiority. It focuses on the development of algorithms and software technologies that identify and integrate informational content from multiple sources, leading to decision aids that support user-cognitive processes. Because persistent sensors are generating massive amounts of data, the focus is on technologies that not only integrate information from diverse sources, but also provide indications of information significance in ways that support the user's decision needs, regardless of location and operational situation. To achieve this, it must be possible to automate understanding of the battlespace by identifying objects, determining relationships among the objects, assessing intent, and automatically generating courses of action with associated risks and uncertainty. Effort will also be devoted to developing technology for increasing assurance and security for C3 information systems and technology for improving information discovery and information presentation in such systems. The Nano Electronics Technology activity is focused on developing ultra-low power, higher performance computing devices and components that are based on novel functionalities of nanometer scale materials and are enabled by improved understanding of nanomaterials, new devices and circuit design concepts, as well as new architectures uniquely suited for nanoscale systems. Effective in FY 2013, this activity title has been changed from Computational Framework and Methods for Rapid Accurate Decision Making to Applied Information Sciences for Decision Making in order to completely capture the work being performed. The current specific objectives are: a) Data Understanding (Formerly: Automated Intelligence Tools): Develop automated, image and signal intelligence understanding tools based on rigorous mathematical and statistical methods that lead to improved change detection, improve object and activity detection and recognition capabilities, context and scene understanding, and inferring of the threat levels to support decision making and persistent and adaptive surveillance. b) Information Integration (Formerly; Battlespace Sensor and Intelligence Integration): Develop innovative methods for combining traditional and non-traditional data from sensors and disparate sources to provide the best estimate of objects, events, and conditions in the battlespace, in terms of their identity, associated error or uncertainty, context, impact, while inferring relationships and their intentions. c) Mission Focused Autonomy (MFA): Develop proactive situational awareness and rapid decision making applications and analytics with information PUSH as well as PULL, where joint human controlled and automated analytic processes can collaboratively work together to solve tactical and strategic problems within a multi-level, secure environment. The MFA system contains the following elements: a) access to enterprise level structured and unstructured data repositories and automated search and discovery of evidence collected across these heterogeneous databases; b) analytics that automate the ability to infer the meaning of evidence that is discovered; c) structured process (hypothesis or argument) that provides context in order to constrain and guide the search and analytic techniques toward goals that are focused on proving the hypothesis right or wrong; d) knowledge repository that maintains pedigree and state of hypothesis satisfaction or refutation; e) Collaborative environment wherein all analytic participants can share the state of hypothesis satisfaction and collectively contribute evidence data to solve the common problem. Develop rigorous and efficient methods for building sophisticated situational models, and develop automated reasoning techniques to categorize and recognize situations under a variety of conditions leading to methods that predict situations under different settings. d) Resource Optimization (Formerly: Automated Decision Tools): Develop automated decision tools based on mathematically rigorous techniques (e.g., mathematical optimization) that support decision-making to ensure the best use of scarce and/or expensive resources, achieving optimal allocations for large complex scenarios, including ones that contain uncertainty, in drastically reduced amounts of time. Develop methods that support decision making in networked sensor management and allocation to ensure sensor assets are deployed in an optimal, or near optimal, manner. e) Trusted Systems & Networks (Formerly: Secure Sensor Networks): Develop tools and methods to securely handle information without exposing intelligence information about the networks or systems to adversaries. f) Nanoscale Electronics: To develop novel nanometer scale (feature size near or below 10nm) logic/memory devices and related circuits and architectures to deliver ultra-low power, light weight and high performance computational capability for autonomous vehicles and individual warfighters. Effective in FY 2014, Nanoscale Electronics has been transferred from Electromagnetic Systems Applied Research to Applied Information Sciences for Decision Making in order to completely capture the work being performed. The decrease from FY 2012 to FY 2013 is a result of the realignment of funds and associated Radar and Surveillance efforts to Multi-Source Integration and Combat Identification activity. These efforts are more closely aligned to the objectives of this activity. The increase from FY 2013 to FY 2014 is a result of the expanded investment in Mission Focused Autonomy research and the transfer of requirements and associated funding for Nanoscale Electronics Research from PE 0602271N. The following are non-inclusive examples of accomplishments and plans for projects funded in this activity.
Document Details
- Document Type
- Accomplishment
- Publication Date
- Oct 01, 2014
- Source ID
- e695a6eb514e2128f929a000229178fa