Autonomous AI Agents in Economic Environments: An Experimental Agent-Based Framework

This project investigates architectures of autonomous AI agents capable of identifying economic opportunities in digital environments, adapting their toolsets, and generating value through web-based services and EVM-compatible infrastructure utilizing account abstraction (ERC-4337). The research develops an experimental sandbox that combines agent economies, tokenomic incentive mechanisms, and reputation systems to evaluate profitability, service quality, autonomy, robustness, and coordination dynamics within multi-agent environments. The framework enables controlled experimentation with economic behavior, adaptation strategies, and interactions between autonomous agents operating under varying constraints and governance conditions. A central objective is the creation of a reproducible and observable agent-economy framework in which the behavior of autonomous AI systems can be systematically measured, analyzed, and validated through transparent metrics, formal constraints, and safety-oriented governance mechanisms.