Ev-Trust: An Evolutionary Stable Trust Mechanism for Decentralized LLM-Based Multi-Agent Service Economies

TL;DR

Ev-Trust is a novel trust mechanism for decentralized LLM-based multi-agent systems that uses evolutionary game theory to promote cooperation and prevent systemic trust collapse.

Contribution

It introduces Ev-Trust, a strategy-equilibrium trust mechanism based on evolutionary game theory, ensuring stability and cooperation among autonomous agents.

Findings

Eliminates malicious strategies effectively

Enhances collective revenue

Resilient against mutant behaviors

Abstract

Autonomous LLM-based agents are increasingly engaging in decentralized service interactions to collaboratively execute complex tasks. However, the intrinsic instability and low-cost generativity of LLMs introduce a systemic vulnerability, where self-interested agents are incentivized to pursue short-term gains through deceptive behaviors. Such strategies can rapidly proliferate within the population and precipitate a systemic trust collapse. To address this, we propose Ev-Trust, a strategy-equilibrium trust mechanism grounded in evolutionary game theory. Ev-Trust constructs a dynamic feedback loop that couples trust evaluation with evolutionary incentives, embedding interaction history and reputation directly into the agent's expected revenue function. This mechanism fundamentally reshapes the revenue structure, converting trustworthiness into a decisive survival advantage that suppresses short-sightedness. We provide a rigorous theoretical foundation based on the Replicator Dynamics, proving the asymptotic stability of Evolutionary Stable Strategies (ESS) that favor cooperation. Experimental results indicate that Ev-Trust effectively eliminates malicious strategies and enhances collective revenue, exhibiting resilience against the invasion of mutant behaviors.