Opportunity |
|
DoD Communities of Interest |
R&D Research and Development |
Subject |
DARPA BAA HR001120S0034: Strategic Technologies |
Due Date |
31 October 2021 |
Government Organization |
DEFENSE ADVANCED RESEARCH PROJECTS AGENCY (DARPA) |
Description 1.1 PROGRAM OVERVIEW It is becoming evident that the U.S. cannot solve this dilemma by continuing legacy practices of building the next bigger, faster, more powerful, more survivable version of what came before. A new paradigm is needed that values “lethality” over monolithic system dominance. Whereas dominance is measured by comparing capabilities across systems, lethality is measured by the ability to deliver the desired effect at will, regardless of the system or systems of systems involved. DARPA/STO aims to provide the U.S. military lethality using Mosaic Warfare strategy: fast, scalable, adaptive joint multi-domain lethality. The disaggregation of effects chain functions (e.g., Find, Fix, Target, Track, Engage, and Assess or F2T2EA) across a heterogeneous mix of manned and unmanned platforms from all domains. Furthermore, it can compose and recompose effects chains at high speed without prior knowledge of which systems will provide which function(s) of a given effects chain. The result presents an adversary with an overwhelming, diverse set of kinetic and non-kinetic decision dilemmas without common counters or failure modes. To achieve this ambitious vision, DARPA/STO is seeking innovative ideas and disruptive technologies within the focus areas of the broader Mosaic Warfare objective: Force Composition: How should a commander provision assets for the battle? What elements should be used to deliver the desired effect? How should these assets be organized? How can we understand logistics flow and readiness to know how and when these assets will be available? How can the probability of success of a given effects chain be “verified” against situation uncertainties? Strategy and Mission Planning: How would different effects chains be employed at different times during a campaign? What information is needed to make these decisions and plan the effects? How can this information be acquired? Communications: Task Planning: How do we develop fine-scale tactics automatically? Can these fine-scale tactics learn and adapt to the combat situation? How should tasks be assigned to specific systems (e.g., within a swarm or constellation)? How can this tasking and supporting information be translated into a message framework each system will understand? How can both autonomous machines and human combat units maintain coherent task coordination and execute missions at the edge when communications are degraded or denied? Training: How will human warfighters operate with new mosaic elements without prior training? Are there novel ways to train Artificial Intelligence (AI) synergistically with the human operator's training to instill human context and intuition into the AI while avoiding human bias? How can we train human operators to fast and minimize operator burden? Can new systems be developed with streamlined, more intuitive human-machine interfaces? How can more of the mechanical tasks of operating a new system (i.e., “button pushing”) be automated to minimize learning requirements and enable warfighters to focus on more cognitive functions? How can we enable humans and machines to share tasks at the edge? What are approaches to managing the level of 1.1.2 Mosaic Effects Web Services (EWS) |
|
Website |
https://beta.sam.gov/opp/7b3237fc6a984a8aab3f131e392f41ad/view |
|
|