@inproceedings{qian-etal-2026-wonderecon,
title = "{W}onder{E}con: An Interactive {LLM}-Agent System for Simulating Economies",
author = "Qian, Jing and
Liu, Boyu and
Gu, Wenyuan and
Ruan, Hang and
Huo, Cheng and
Yang, Junjie and
Deng, Mingyu and
Han, Jiale and
Wang, Benyou",
editor = "Agrawal, Sweta and
Abad, Alberto",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-demos.77/",
pages = "818--829",
ISBN = "979-8-89176-461-3",
abstract = "How an economic shock propagates through the heterogeneous decisions of diverse economic roles and emerges as aggregate fluctuations is a central question in economics. Traditional agent-based models hard-code behavioral rules and cannot read language, while recent LLM-agent simulations often omit explicit belief formation, endogenous price formation, or mechanism-grounded state transitions, and rarely let a human step into the loop. We present WonderEcon, a configurable, LLM-driven yet economic-rule-grounded multi-agent simulation system in which households, firms, commercial banks, a central bank, and a government interact across five markets, forming a self-consistent macroeconomic loop. Every agent decides through a four-step natural-language pipeline, reading real news alongside structured data, with every step observable. A player mode, with dedicated scene and character modeling, lets a human take over one household agent, yielding a counterfactual comparison and the Economic Personality Type Indicator (EPTI). On an interest-rate hiking cycle, WonderEcon demonstrates directional plausibility with respect to six well-known economic principles across four LLMs, and 33 participants find the player system satisfying. The engine and interfaces are publicly available."
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%0 Conference Proceedings
%T WonderEcon: An Interactive LLM-Agent System for Simulating Economies
%A Qian, Jing
%A Liu, Boyu
%A Gu, Wenyuan
%A Ruan, Hang
%A Huo, Cheng
%A Yang, Junjie
%A Deng, Mingyu
%A Han, Jiale
%A Wang, Benyou
%Y Agrawal, Sweta
%Y Abad, Alberto
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-461-3
%F qian-etal-2026-wonderecon
%X How an economic shock propagates through the heterogeneous decisions of diverse economic roles and emerges as aggregate fluctuations is a central question in economics. Traditional agent-based models hard-code behavioral rules and cannot read language, while recent LLM-agent simulations often omit explicit belief formation, endogenous price formation, or mechanism-grounded state transitions, and rarely let a human step into the loop. We present WonderEcon, a configurable, LLM-driven yet economic-rule-grounded multi-agent simulation system in which households, firms, commercial banks, a central bank, and a government interact across five markets, forming a self-consistent macroeconomic loop. Every agent decides through a four-step natural-language pipeline, reading real news alongside structured data, with every step observable. A player mode, with dedicated scene and character modeling, lets a human take over one household agent, yielding a counterfactual comparison and the Economic Personality Type Indicator (EPTI). On an interest-rate hiking cycle, WonderEcon demonstrates directional plausibility with respect to six well-known economic principles across four LLMs, and 33 participants find the player system satisfying. The engine and interfaces are publicly available.
%U https://aclanthology.org/2026.emnlp-demos.77/
%P 818-829
Markdown (Informal)
[WonderEcon: An Interactive LLM-Agent System for Simulating Economies](https://aclanthology.org/2026.emnlp-demos.77/) (Qian et al., EMNLP 2026)
ACL
- Jing Qian, Boyu Liu, Wenyuan Gu, Hang Ruan, Cheng Huo, Junjie Yang, Mingyu Deng, Jiale Han, and Benyou Wang. 2026. WonderEcon: An Interactive LLM-Agent System for Simulating Economies. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 818–829, Budapest, Hungary. Association for Computational Linguistics.