# WES: Agent-based User Interaction Simulation on Real Infrastructure

arXiv: https://arxiv.org/abs/2004.05363 · HTML: https://mlsanity.com/paper/2004.05363/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2020.

## Built on by (most cited first, 8 of 8)

- [RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems](https://mlsanity.com/paper/2103.08057/) (2021)
- [Modelling Cooperation in Network Games with Spatio-Temporal Complexity](https://mlsanity.com/paper/2102.06911/) (2021)
- [Investigating Tax Evasion Emergence Using Dual Large Language Model and Deep Reinforcement Learning Powered Agent-based Simulation](https://mlsanity.com/paper/2501.18177/) (2025)
- [Harden and Catch for Just-in-Time Assured LLM-Based Software Testing: Open Research Challenges](https://mlsanity.com/paper/2504.16472/) (2025)
- [Breaking Single-Tester Limits: Multi-Agent LLMs for Multi-User Feature Testing](https://mlsanity.com/paper/2506.17539/) (2025)
- [Just-in-Time Catching Test Generation at Meta](https://mlsanity.com/paper/2601.22832/) (2026)
- [Prismal view of ethics](https://mlsanity.com/paper/2205.13370/) (2022)
- [Social and Ethical Risks Posed by General-Purpose LLMs for Settling Newcomers in Canada](https://mlsanity.com/paper/2407.20240/) (2024)

## Abstract (arXiv)

We introduce the Web-Enabled Simulation (WES) research agenda, and describe FACEBOOK's WW system. We describe the application of WW to reliability, integrity and privacy at FACEBOOK , where it is used to simulate social media interactions on an infrastructure consisting of hundreds of millions of lines of code. The WES agenda draws on research from many areas of study, including Search Based Software Engineering, Machine Learning, Programming Languages, Multi Agent Systems, Graph Theory, Game AI, and AI Assisted Game Play. We conclude with a set of open problems and research challenges to motivate wider investigation.