| 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. | |