Defense Advanced Research Projects AgencyTagged Content List

Harnessing Complexity

Systems comprising multiple and diverse interactions

Showing 34 results for Complexity + News RSS
In today’s rapidly evolving mission environments, warfighters need new vehicles, weapons and other systems fielded quickly. Current design and development approaches, however, are unable to deliver those systems in a timely manner. To help overcome these challenges, DARPA’s Adaptive Vehicle Make (AVM) portfolio of programs is working to develop revolutionary approaches for the design, testing and manufacturing of complex defense systems, with the goal of shortening development timelines by five times or more. Thanks to strong early test results and a new opportunity to transition the technology, DARPA has decided to speed its current AVM successes to the defense industrial base in 2014—years earlier than originally planned.
Scientists and engineers in DARPA’s Defense Sciences Office (DSO) promote and exploit new discoveries across the frontiers of physics, chemistry, and mathematics to identify and accelerate potentially game-changing technologies for U.S. national security. After recently spinning off biological technologies into a new office, DSO’s investment portfolio, which continues to create new materials and explore the boundaries of physical phenomena, is expanding to include novel approaches to understanding, predicting, designing, and developing engineered complex systems.
The exponential growth of diverse science data represents an unprecedented opportunity to make substantial advances in complex science and engineering, such as discovery of novel materials or drugs. However, without tools to unify principles, results, models and other kinds of data into a single computational representation, it is difficult to relate data from any one scientific problem or area to the broader body of knowledge.
Uncertainty is sometimes unavoidable. But in the world of scientific computing and engineering, at least, what’s worse than uncertainty is being uncertain about how uncertain one is.
Whether designed to predict the spread of an epidemic, understand the potential impacts of climate change, or model the acoustical signature of a newly designed ship hull, computer simulations are an essential tool of scientific discovery. By using mathematical models that capture the complex physical phenomena of the real world, scientists and engineers can validate theories and explore system dynamics that are too costly to test experimentally and too complicated to analyze theoretically.