SBIR/STTR Research Award
The Future of Wargaming: Collaborative Multi-Agent Reasoning
Award amount
$139,709Program and phase
SBIR · Phase IAward year
2025Award details
- Awarding agency
- Department of Defense
- Branch
- Navy
- Recipient company
- Pytho AI
- Proposal award date
- 2025-07-07
- Contract end date
- 2026-01-07
- UEI
- DOD1QdTXIAYO
- Solicitation number
- 25.1
- Topic code
- N251-065
Research abstract
Technical AbstractThe Department of Defense (DoD) is implementing a strategic shift away from the Global War on Terror to prioritize addressing the challenges posed by Great Power Competition (GPC) with near-peer and peer threats. Wargaming prepares warfighters for this new, modern battlefield that demands rapid and informed decision-making through unbiased, realistic, and adaptive scenarios. Currently, wargaming involves a diverse team of decision-makers, analysts, and warfighters that invest significant time and resources into anticipating adversarial strategies and tactics. However, this human-centric approach is vulnerable to costly errors, biases, and omissions, which can seriously undermine the assessment of evidence, statistical analysis, and the understanding of cause and effect. As warfare environments scale across Multi-Domain Operations, traditional manual wargaming methods will struggle to keep pace with the realities of conflict.ÝÝÝTo address this critical readiness need, Pytho proposes the development of a Wargaming Adaptive Reasoning System (WARS) ñ an engine powered by advanced AI Agents collaborating with human experts ñ to facilitate real-time decision-making, dynamic scenario adjustments, and comprehensive Course of Action (COA) evaluations. By leveraging the collective intelligence of a network of specialized AI Agents working alongside human experts, the system will deliver enhanced situational understanding, faster scenario resolution, and superior mission planning outcomes.
Technology keywords
Not reported
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
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