---
language:
  - en
tags:
  - technical-report
  - preprint
  - world-model
  - digital-agents
---

# World Intelligence Agent: Unifying World Modeling and Action Learning for Digital Agents

**Darwin Agent Team** | **Technical Report / Preprint**

## Read the report

- [Read or download the full technical report (PDF)](https://huggingface.co/darwinagent/WIA-Technical-Report/resolve/main/Tech_Report__WAM.pdf)
- [Browse the PDF file](https://huggingface.co/darwinagent/WIA-Technical-Report/blob/main/Tech_Report__WAM.pdf)
- [Project page](https://darwin-agent.github.io/WIA/)

## Overview

World Intelligence Agent (WIA) unifies world modeling and action learning for digital agents.
The report introduces WIA-Corpus and WIA-Bench, presents the WIA-WM family of world models,
and explores simulation-based training, inference lookahead, and the WIA-WAM extension for
action generation.

Please refer to the full report for the methods, experimental protocols, results, and limitations.

This repository hosts the technical report only; it does not contain model weights or executable code.