SRAP-Agent: Simulating and Optimizing Scarce Resource Allocation Policy with LLM-based Agent

TL;DR

An innovative framework, SRAP-Agent (Simulating and Optimizing Scarce Resource Allocation Policy with LLM-based Agent), which integrates Large Language Models (LLMs) into economic simulations, aiming to bridge the gap between theoretical models and real-world dynamics is proposed.

Abstract

Public scarce resource allocation plays a crucial role in economics as it directly influences the efficiency and equity in society. Traditional studies including theoretical model-based, empirical study-based and simulation-based methods encounter limitations due to the idealized assumption of complete information and individual rationality, as well as constraints posed by limited available data. In this work, we propose an innovative framework, SRAP-Agent (Simulating and Optimizing Scarce Resource Allocation Policy with LLM-based Agent), which integrates Large Language Models (LLMs) into economic simulations, aiming to bridge the gap between theoretical models and real-world dynamics. Using public housing allocation scenarios as a case study, we conduct extensive policy simulation experiments to verify the feasibility and effectiveness of the SRAP-Agent and employ the Policy Optimization Algorithm with certain optimization objectives. The source code can be found in https://github.com/jijiarui-cather/SRAPAgent_Framework

Figures (9)

• Figure 1: An illustration of the SRAP-Agent framework. The horn symbolizes the broadcasting process of policy information to participants.
• Figure 2: Comparison of queue sorting methods.
• Figure 3: Deceptive behavior and cooperation behavior. Max's conservative personality and lack of trustworthy acquaintances lead him to conceal his true intentions when sharing information. In contrast, Sarah seeks advice on choosing a house from her friends and openly shares her housing preferences.
• Figure 4: The average $f(\pi)$ for optimized policies with respect to the iteration number.
• Figure 5: The overall schematic diagram of two communication modes. The direction-ed arrow carries the message $u_{ij}$ from $p_{i}$ to $p_{j}$'s mailbox. The blog represents the chatting platform.