Description
The Decentralized Artificial Intelligence through Controlled Emergence (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. The program aims to move beyond brittle, centralized orchestration and harness the scalability and adaptability of self-organizing systems. The key areas of focus include decentralized coordination, local control of individual agents, and the development of a local adaptor that can interface with any agent. The program will demonstrate DICE architectures in simulation environments, targeting measurable gains in scalability, adaptability, resilience, and long-horizon role coherence.
Some of the key features of the program include:
• Decentralized coordination of heterogeneous AI agents
• Local control of individual agents to maintain role coherence and mission alignment
• Development of a local adaptor to interface with individual agents
• Demonstration of DICE architectures in simulation environments
• Focus on scalability, adaptability, resilience, and long-horizon role coherence
The program is a 36-month effort with three technical areas (TAs): TA1 for peer-to-peer coordination, TA2 for local control, and TA3 for testing and evaluation. Proposals are invited to address one or more of these TAs, and the program encourages innovative and disruptive approaches to achieve the program's goals.