arXiv:2606.02859v1 Announce Type: new Abstract: How can a population of agents self-orchestrate and self-adapt into stronger collective intelligence without centralized control? Inspired by Friedrich Hayek's economic theory of decentralized coordination in markets, we study this question through an agent economy in which agents compete via auctions for the right to act, exchange payments, and accumulate wealth from environmental rewards. These simple economic signals induce decentralized credit assignment, driving planning without global orchestration or explicit communication protocols. The p
The accelerating development of advanced AI models and the increasing complexity of multi-agent systems necessitate new paradigms for decentralized and self-organizing intelligence, drawing inspiration from established economic theories.
This research outlines a framework for emergent collective intelligence in AI agents through economic interactions, potentially leading to more robust and scalable autonomous systems without centralized control.
The proposed 'Economy of Minds' shifts how we conceive of orchestrating multi-agent AI, moving from explicit communication protocols to decentralized economic incentives for coordination and self-adaptation.
- · AI agents developers
- · Decentralized autonomous organizations (DAOs)
- · Researchers in complex adaptive systems
- · Developers of competitive AI environments
- · Centralized AI orchestration systems
- · AI models requiring extensive explicit communication
- · Developers focused solely on top-down AI control
- · Traditional command-and-control AI architectures
Economic mechanism design becomes a critical component in future multi-agent AI system development.
This approach could enable more resilient and adaptable AI systems in dynamic and unpredictable environments, such as autonomous supply chains or advanced robotic teams.
The principles of 'Economy of Minds' may inspire new forms of human-AI collaboration and governance models for complex digital ecosystems.
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