nonogram-gymnasium
Python package implementing Nonogram as an Gymnasium environment.
RL environments
nonogram-gymnasium
Experimental environment
A compact Gymnasium environment for learning to solve Nonogram puzzles from row and column clues.
- Problem
- Structured puzzles provide small, inspectable decision problems for exploring observations, rewards, and agent behavior.
- Approach
- A hidden binary grid, clue-based observations, and cell/value actions exposed through Gymnasium reset and step interfaces.
- Implemented
-
- Seeded puzzle generation, configurable board size and episode length, rendering, and explicit termination/truncation behavior.
- Random-agent and terminal-play examples, a notebook demo, and a DQN training example using an action wrapper.
- Engineering
- Environment and reward tests; linting, formatting, and typing checks in CI across Python 3.10–3.12.
Scope. A toy research environment with a simple reward function and no correction action for previously played cells.