https://github.com/tyleryep/wolfbot

One Night Ultimate Werewolf: AI Edition
https://github.com/tyleryep/wolfbot

ai deep-learning game one-night player reinforcement-learning simulator

Last synced: about 1 year ago
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One Night Ultimate Werewolf: AI Edition

• Host: GitHub
• URL: https://github.com/tyleryep/wolfbot
• Owner: TylerYep
• License: mit
• Created: 2018-05-01T07:45:05.000Z (about 8 years ago)
• Default Branch: main
• Last Pushed: 2025-05-05T18:44:39.000Z (about 1 year ago)
• Last Synced: 2025-05-05T19:53:03.163Z (about 1 year ago)
• Topics: ai, deep-learning, game, one-night, player, reinforcement-learning, simulator
• Language: Python
• Homepage:
• Size: 6.47 MB
• Stars: 9
• Watchers: 0
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# WolfBot

### One Night Ultimate Werewolf: AI Edition

By Tyler Yep & Harry Sha

[![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/release/python-3120/)

[![Build Status](https://github.com/TylerYep/wolfbot/actions/workflows/test.yml/badge.svg)](https://github.com/TylerYep/wolfbot/actions/workflows/test.yml)

[![GitHub license](https://img.shields.io/github/license/TylerYep/wolfbot)](https://github.com/TylerYep/wolfbot/blob/main/LICENSE)

[![codecov](https://codecov.io/gh/TylerYep/wolfbot/branch/main/graph/badge.svg)](https://codecov.io/gh/TylerYep/wolfbot)

## Introduction

This is an implementation of the popular board game One Night Ultimate Werewolf.

To try it out, run `python main.py` in the terminal.

(You may need to run `pip install -r requirements.txt` first.)

Constants, along with their use cases, are listed in wolfbot/const.py. You can change:

- \# of players

- \# of center cards

- Which roles are used

- Behavior of AI players on the Werewolf Team / Village Team

## Interactive Mode

To play the game yourself as a character, use the `-u` / `--user` flag:

```

python main.py --user

```

To replay a game, add the `-r` / `--replay` flag.

```

python main.py --user -r

```

To examine verbose output of a game, use the `-l` / `--log_level` flag.

```

python main.py -l trace

```

## Simulating Games

To simulate many runs of the game, use the `-n` flag.

```

python main.py -n 100

```

or use the profiler:

```

python profiler.py

```

For additional information, please check out the GitHub Wiki!

# Contributing

All issues and pull requests are much appreciated!

- First, run `pre-commit install`.

- To see test coverage scripts and other auto-formatting tools, use `pre-commit run -a`.

- To run all tests, run `pytest`.

- To only run unit tests, run `pytest tests/unit_test`.

- To only run integration tests, run `pytest tests/integration_test`.