R-2A Activity · President's Budget PB2027

Decision Making

FY2027 Request
$21.2M
▲ 4.9% vs FY2026
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This activity requests $21.2M in FY2027, 22% of project 613003, up 4.9% on FY2026. The R-2A exhibit describes it across FY2026–FY2027, including what the FY2027 money is planned to buy.

FY2027 Request
$21.2M
▲ 4.9% vs FY2026
FY2026 Enacted
$20.2M
▼ 6.6% vs FY2025
FY2025 Actual
$21.7M
Prior year
Planned work

What the FY2027 request buys

Verbatim from the R-2A exhibit for project 613003 of PE 0601102F. This is the budget justification's own description of work that has not happened yet — the one thing no other level of the budget carries.

FY2027 planned work

- Continue investigating new mathematical laws, scientific principles, and robust algorithms that underlie intelligent, mixed human-machine decision-making to achieve accurate real-time integration of human expertise and knowledge into a machine-based battlespace network. - Continue to develop new mathematical models for information capture; object, scene and relation identification; and multi-level reasoning and meta-learning. - Continue to advance the critical knowledge base in modeling of individual and group cognitive processing and decision making, and construct advanced methodologies for predictive, verifiable simulations of large-scale socio-cultural and human-machine hybrid networks.

FY2026 to FY2027 change

FY 2027 increased compared to FY 2026 by $0.986 million due to minor programmatic adjustments to the DAF Science and Technology portfolio.

Before the request year

FY2026: the year under way

Prior-year accomplishments and current-year plans from the same exhibit. Context for the FY2027 plan, not a series — an activity partitions its project exactly in the request year, but can under-cover it in earlier years.

FY2026 plans — current year

- Investigate new mathematical laws, scientific principles, and robust algorithms that underlie intelligent, mixed human-machine decision-making to achieve accurate real-time integration of human expertise and knowledge into a machine-based battlespace network. - Develop new mathematical models for information capture; object, scene and relation identification; and multi-level reasoning and meta-learning. - Advance the critical knowledge base in modeling of individual and group cognitive processing and decision making, and construct advanced methodologies for predictive, verifiable simulations of large-scale socio-cultural and human-machine hybrid networks.

Money

Three years, and no five-year plan

An R-2A activity publishes the prior year, the current year and the budget year. The FYDP outyears exist at project and program-element level and are deliberately absent here rather than inferred. Estimate types are colored and never summed into one figure.

021.7FY25ACTUAL20.2FY26ENACTED21.2FY27REQUEST
Actual Enacted Request
Fiscal YearEstimate TypeAmount ($M)
FY2025Actual21.7
FY2026Enacted20.2
FY2027Request21.2

This activity is 22% of project 613003's FY2027 request and 7.2% of PE 0601102F's. In the request year the activities under a project sum to it exactly; in the current year they under-cover it in about 9% of cases, so an activity's delta can legitimately exceed its parent's and the two must not be compared row to row.

Where this sits

4 activities in project 613003

Every R-2A line of this project, largest FY2027 request first. Linked where the activity has enough of its own narrative to carry a page; the rest are shown in full on the project page.

Source
FY2027 Department of the Air Force RDT&E Budget Justification · Exhibit R-2A · PE 0601102F, project 613003 (President's Budget PB2027). Congressional marks are recorded on the program element, never on an activity.
Machine access
Markdown twin /programs/0601102F/613003/a1.md · MCP mcp.hitchintel.combudget_get_activity