Custom Environment

This guide explains how to create your own environment for VAGEN.

Overview

VAGEN environments extend GymImageEnv, which provides a simple API for multi-modal (image + text) observations.

Step 1: Create Your Environment Class

Use GymImageEnv as the base class:

• vagen/envs/gym_image_env.py

Refer to Sokoban for a full implementation example:

• vagen/envs/sokoban/sokoban_env.py

Step 2: Register the Environment

Add your environment entry to vagen/configs/env_registry.yaml:

env_registry:
  Sokoban: vagen.envs.sokoban.sokoban_env.Sokoban
  FrozenLake: vagen.envs.frozenlake.frozenlake_env.FrozenLake
  MyEnv: vagen.envs.myenv.my_env.MyEnv  # Add this line

Step 3: Create Configuration Files

Prepare training and validation configs:

• train.yaml
• val.yaml

You can follow the Sokoban examples as templates:

• examples/sokoban/train_sokoban_vision.yaml
• examples/sokoban/val_sokoban_vision.yaml

Step 4: Create a Training Script

Write your training script based on examples/sokoban/train_ppo_qwen25vl3b.sh