How can we build trustworthy AI agent economies?
Governing the Agent-to-Agent Economy of Trust via Progressive Decentralization
This paper proposes a system for governing interactions and value exchange between autonomous AI agents using a decentralized, blockchain-based approach. It introduces AgentBound Tokens (ABTs), non-transferable credentials tied to individual agents, analogous to Soulbound Tokens for humans. ABTs track agent behavior and are staked as collateral for actions, incentivizing ethical behavior through automated penalties for misconduct. Key points for LLM-based multi-agent systems include the use of ABTs for identity, reputation management, and access control; the concept of staking ABTs for participation in tasks; and the role of decentralized governance and human oversight in ensuring responsible agent behavior. The system aims to create a self-sustaining trust economy where agents build reputation through ethical actions, enabling complex collaboration and resource allocation within the multi-agent system.