README.md

---
title: Agentic World Model Explorer
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 4.36.0
app_file: app.py
pinned: false
---

# Agentic World Model Explorer

An interactive exploration of the "levels x laws" taxonomy from the Agentic World Modeling paper (2604.22748).

## What This Does

Demonstrates the three capability levels of world models:
- **L1 Predictor**: One-step local transitions
- **L2 Simulator**: Multi-step action-conditioned rollouts
- **L3 Evolver**: Self-revising models that update from prediction failures

Across four law regimes:
- Physical (object manipulation, physics)
- Digital (web/GUI agents, software)
- Social (multi-agent coordination)
- Scientific (experimental design)

## Hypothesis

World models with explicit structured state representations (L2+) demonstrate better compositional generalization than pure next-token predictors when evaluated on out-of-distribution scenarios within the same law regime.

## Findings

See the live demo for interactive examples of state representation strategies and their impact on generalization.