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ARC-AGI-3 games are turn-based systems where agents interact with 2D grid environments through a standardized action interface. Each game maintains state through discrete action-response cycles.
  • Agents will receive a 1-N frames of JSON objects with the game state and metadata.
  • Agents will respond with an action 1-5 or a 6th action which includes x, y coordinates.

Available Games

To see which games are available, either go to arcprize.org/tasks or make an API call to list games. Example games include
  • ls20 - Agent reasoning
  • ft09 - Elementary Logic
  • vc33 - Orchestration

Game ID

Game IDs are formatted as <game_name>-<version>. game_names are stable, but version may change as games update.

Grid Structure

  • Dimensions: Maximum 64x64 grid size
  • Cell Values: Integer values 0-15 representing different states/colors
  • Coordinate System: (0,0) at top-left, (x,y) format

Game Available Actions

Each game provides an explicit set of actions that an agent can take. Actions available vary per game. Typically, the available actions include:
  • Actions 1–4: ex: move up, down, left, or right
  • Action 6: A complex action (if supported by the game)
To learn more about each action and what it does, please visit the Actions.

Running a Full Playtest

To run a complete playtest, you’ll need to integrate your agent with scorecard management and the game loop. This is what happens “under the hood” when you run commands like uv run main.py --agent=random --game=ls20 (from the Quick Start). Below is pseudocode for the key steps. For a ready-to-use implementation, see the Swarms guide—which can automate this for you across multiple games.

Game State Enumeration

Full Playtest

This is a bare-bones example for (educational purposes) is also available as a notebook.
This workflow ensures your plays are tracked officially. For parallel playtests across games, use a swarm to handle the orchestration automatically.