Decentralized Artificial Intelligence through Controlled Emergence (DICE)
| Location: |
Federal |
| Posted: |
Jul 14, 2026 |
| Due: |
Aug 25, 2026 |
| Agency: |
DEPT OF DEFENSE |
| Type of Government: |
Federal |
| Category: |
- A - Research and development
|
| Solicitation No: |
HR001126S0010 |
| Publication URL: |
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Decentralized Artificial Intelligence through Controlled Emergence (DICE)
Active
Contract Opportunity
Department/Ind. Agency
DEPT OF DEFENSE
Sub-tier
DEFENSE ADVANCED RESEARCH PROJECTS AGENCY (DARPA)
Office
DEF ADVANCED RESEARCH PROJECTS AGCY
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General Information View Changes
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Contract Opportunity Type: Solicitation (Updated)
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Updated Published Date: Jul 14, 2026 11:17 am EDT
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Original Published Date: Jun 10, 2026 10:07 am EDT
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Updated Date Offers Due: Aug 25, 2026 02:00 pm EDT
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Original Date Offers Due: Aug 25, 2026 02:00 pm EDT
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Inactive Policy: Manual
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Updated Inactive Date: Sep 24, 2026
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Original Inactive Date:
Sep 24, 2026
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Initiative:
Classification
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Original Set Aside:
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Product Service Code: AC11 - NATIONAL DEFENSE R&D SERVICES; DEPARTMENT OF DEFENSE - MILITARY; BASIC RESEARCH
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NAICS Code:
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541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)
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Place of Performance:
Description
The DICE program seeks to develop the theory and algorithms for decentralized coordination and local inference control to enable a scalable, adaptive, and resilient collective of heterogeneous AI agents that can autonomously execute sustained long-time-horizon missions in contested environments while remaining under human control. In contrast to small-scale, rigid, and fragile centralized orchestration or the high-risk unpredictable nature of ad hoc compositions of AI agents, DICE aims to harness the scalability and adaptability of self-organizing systems while minimizing risks and ensuring that the collective behavior remains predictable and aligned with intended outcomes. This approach mirrors the principles of decentralized self-organization that underpin the internet's own scalability and resilience, where robust global behavior emerges from simple, local rules.
Attachments/Links
Contact Information
Contracting Office Address
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675 NORTH RANDOLPH STREET
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ARLINGTON , VA 222032114
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USA
Secondary Point of Contact
History
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