“Self-Replicating Evolutionary Agentic AI Swarming Force” with Autonomous Embedded AI Guardrail Enforcers

U.S. Department of Defense – Navy (SBIR)

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Funder
U.S. Department of Defense – Navy (SBIR)
Award amount
Not specified
Deadline
January 6, 2027
Eligible countries
United States
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Summary

SBIR topic DON27BZ02-NV012 (U.S. Department of Defense – Navy), Phase I and II. Open to U.S. small businesses. Opens: December 2, 2026. Closes: January 6, 2027. This SBIR topic seeks hardware-agnostic Agentic AI swarm-teaming technologies capable of self-replication, hybrid-evolution (self-evolution and coevolution), and self-organization into teaming many arrangements. It is important to note that this project does not challenge the importance of physical platforms/machines (i.e., unmanned assets) that have physical presence in operational environments. The envisioned Agentic AI system is the machine’s intelligent autonomy software that controls the platform’s presence and its interactions with entities in the operational environment. It autonomously configures individual swarms with unique missions and networks of collaborative swarms operating in multiple operational domains with specific teaming assignments. The envisioned swarm system is agentic as it pursues goals autonomously. It interprets assigned mission objectives and determines how to achieve them. It knows how to process, fuse, and exploit all source intelligence (ASI) and live sensor feeds to determine the course of action (CoA) and keeps adjusting it until the outcome is reached. It decides which payloads to use and when to use them, for example, active and/or passive intelligence, surveillance, reconnaissance, and targeting (ISRT) sensors, point-to-point or omni-broadcast communication, or weapon systems, etc. It adapts when situations or environmental conditions change, or certain aspects of a plan fail. It can recover from various system failures and processing errors. It is designed with embedded AI-Guardrail-Enforcers to manage, validate, and verify every aspect of the Agentic AI system’s performance and associated risks to ensure that the end-to-end system adheres to established policies set forth by the Department of War and the U.S. Navy including operational safety requirements as well as…

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