Defense Advanced Research Projects AgencyTagged Content List

Harnessing Complexity

Systems comprising multiple and diverse interactions

Showing 38 results for Complexity + Programs RSS
The goal of the Mathematics of Sensing, Exploitation and Execution (MSEE) program is to explore and develop high-impact methods for scalable autonomous systems capable of understanding scenes and events for learning, planning, and execution of complex tasks. The program is exploring powerful mathematical frameworks for unified knowledge representation for shared perception, learning, reasoning, and action. One of the central concepts in MSEE is to exploit methods based on minimalist generative grammar, similar to human language, to represent and process visual scenes and actions.
Complex, nonlinear, multiscale dynamical systems are ubiquitous. Examples include weather, fluids, materials, biological systems, communication networks, and social systems. These systems often evolve to a critical state built up from a series of irreversible and unexpected events, which severely limits development and implementation of mathematical models to accurately predict formation and evolution of patterns in such systems.
Certain natural processes perform par excellence computation with levels of efficiency unmatched by classical digital models. Levinthal’s Paradox illustrates this well: In nature, proteins fold spontaneously at short timescales (milliseconds) whereas no efficient solution exists for solving protein-folding problems using digital computing. The Nature as Computer (NAC) program proposes that in nature there is synergy between dynamics and physical constraints to accomplish effective computation with minimal resources.
The explosive growth of global digital connectivity has opened new possibilities for designing and conducting social science research. Once limited by practical constraints to experiments involving just a few dozen participants-often university students or other easily available groups-or to correlational studies of large datasets without any opportunity for determining causation, scientists can now engage thousands of diverse volunteers online and explore an expanded range of important topics and questions.
DARPA's Oceans of Things program seeks to enable persistent maritime situational awareness over large ocean areas by deploying thousands of small, low-cost floats that form a distributed sensor network. Each smart float contains a suite of commercially available sensors to collect environmental data-such as sea surface temperature, sea state, and location - as well as activity data about commercial vessels, aircraft, and even maritime mammals moving through the area. The floats transmit data periodically via satellite to a cloud network for storage and real-time analysis.