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Configurable Operator Decision Models for Constructive Test and Evaluation Simulations

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MDA27BZ02-DV009SBIR / STTR

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The Missile Defense Agency is seeking a Direct-to-Phase-II prototype capability to develop configurable operator decision models for constructive test and evaluation simulations. The goal is to replace fixed scripts and simplified timing rules with AI-enabled representations of human behavior to better understand how operator choices influence the kill chain, including detection, classification, and engagement. The desired solution must feature open, modular interfaces, configurable behavior profiles, and support for Monte Carlo-style analysis, while ensuring decision traceability and explainable outputs. Key deliverables include prototype software, an executable evaluation package, a Phase III transition plan, and comprehensive documentation covering cybersecurity and validation evidence. This solicitation, numbered MDA27BZ02-DV009, is a total small business set-aside. Proposals will be evaluated based on best value, with a primary focus on technical merit, innovation, and the qualifications of the research team, which are weighted more heavily than cost. The contract mandates strict adherence to cybersecurity standards, including CMMC and DFARS 252.204-7012, and requires specific technical document marking to comply with the Arms Export Control Act and the Export Administration Act. All proposals must be submitted via the DoW SBIR/STTR Innovation Portal, with the technical volume limited to 25 pages.

General Info

MDA seeks AI-enabled operator decision models for constructive test and evaluation simulations.

Documents

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PDF, High priority: read this first50 pages · rfp
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PDF, High priority: read this firstrfp
High

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Organization & Contact Information

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AgencyDepartment of Defense → Missile Defense Agency
ContactsNo contacts available
OfficeUSA
Office AddressUSA
ContactsNo contact information available

Full Description

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Government problem: Missile defense test and evaluation rely on constructive simulations to examine large numbers of scenarios, explore operational concepts, evaluate system-of-systems interactions, and reduce risk before live flight events. These simulations can represent physical platforms, sensors, weapons, communications, terrain, and threat laydowns, but operator decision effects are often represented by fixed scripts, simplified timing rules, or manually coded behaviors. This can cause analysis results to overstate or understate operational performance because human choices influence detection, classification, engagement, prioritization, communication, and response timing across the kill chain. Capability gap: The Government lacks a reusable and validated way to generate, configure, execute, and assess operator decision representations across many scenario variations and proficiency levels. Current approaches can require extensive custom programming for each model, scenario, or operator role; may not provide traceable rationale for actions taken during simulation; and may be difficult to compare across test events, analysis teams, or simulation environments. The gap affects the Government’s ability to understand sensitivity to operator behavior, evaluate alternate tactics, and support VV&A with documented evidence of intended use, assumptions, limitations, data pedigree, and risk. Why innovative solutions are likely available: The Government believes innovative small businesses can apply advances from artificial intelligence (AI)-enabled simulation, human behavior representation, synthetic data generation, reinforcement learning, design of experiments, digital engineering, development, security, and operations, and modular simulation integration to address this problem. Related industry capabilities already demonstrate AI-assisted constructive simulation, synthetic data generation, intelligent agents, and integration of commercial simulation toolchains with Government simulation environments. This topic seeks to mature those types of innovations into a Government-purpose capability suitable for missile defense test and evaluation workflows. Government interest: The Government is not seeking a vendor white paper, a visualization-only training game, or a single hard-coded operator model. The Government is seeking a Direct-to-Phase-II prototype capability that can be adapted to multiple missile defense analysis contexts; that can use Government-provided scenarios, models, data, and subject matter expert (SME) input; that can be evaluated against explicit measures of performance and effectiveness; and that can produce artifacts needed for future transition, reuse, and accreditation. Desired characteristics: •Open, modular interfaces for integration with constructive simulations and analysis workflows. •Configurable operator roles and behavior profiles that can be reviewed and adjusted by authorized Government analysts or SMEs. •Support for scenario ensembles, design of experiments, and repeatable Monte Carlo-style analysis. •Decision traceability, data provenance, uncertainty characterization, and explainable outputs suitable for analyst review. Responsible AI, cyber, data-management, and VV&A considerations incorporated from the beginning of Phase II.

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