Equilibrium Dynamics in the Billion-Agent Economy: Autonomous Arbitrage and Market Stability

ABSTRACT

The proliferation of personal autonomous agents capable of executing micro-transactions, negotiating contracts, and performing high-speed arbitrage threatens to upend traditional market stability. We model the 'Billion-Agent Economy' as a massive, decentralized multi-agent reinforcement learning (MARL) environment. Through extensive game-theoretic simulations, we analyze the equilibrium dynamics of agent-to-agent commerce. We find that without standardized latency limits or 'circuit breaker' protocols, agentic swarms naturally converge toward hyper-volatile price oscillations, leading to systemic market flash-crashes. We propose a set of algorithmic regulatory mechanisms designed to ensure fair-trade compliance and stability in hyper-accelerated digital economies.