gobblet-rl 1.2.1

Multi-Agent Reinforcement Learning Environment for the board game Gobblet using PettingZoo.

gobblet-rl

Interactive Multi-Agent Reinforcement Learning Environment for the Gobblet board game using PettingZoo and Pygame.

       

Installation

Using pip (recommended)

pip install gobblet-rl

Local

git clone hhttps://github.com/elliottower/gobblet-rl.git
cd gobblet-rl
pip install -e .

Usage

Setting up a basic environment

In a Python shell, run the following:

from gobblet import gobblet_v1

env = gobblet_v1.env()

Play an interactive game

In the terminal, run the following:

python gobblet/examples/example_user_input.py"

To select a piece size, press a number key 1, 2, or 3, or press space to cycle through pieces. Placing a piece is done by clicking on a square on the board. A preview will appear showing legal moves with the selected piece size. Clicking on an already placed piece will pick it up and prompt you to place it in a new location (re-placing in the same location is an illegal move).

Screen recording of a game

In the terminal, run the following:

python gobblet/examples/example_record_game.py"

This will save a screen recording of a game to gobblet/examples/game.gif

Display a game between two basic CPU agents

In the terminal, run the following:

python gobblet/examples/example_basic.py"

This will launch a game with two agents choosing random actions (other agent types will be added in the future)

Train a DQL agent with Tianshou

In the terminal, run the following:

python gobblet/example_tianshou.py

This will train a DQN model from Tianshou for 50 epochs, and then render the trained agent playing against a random agent in an example match.

Command Line Arguments

Game Modes

example_user_input.py and example_record_game.py take the following arguments:

The default game mode is human vs CPU, with the human playing as red and CPU as yellow.

--player 1 sets the human player as yellow, with the CPU moving first as red.

--cpu-players 0 will launch a game with no CPU agents, taking interactive input for both agents.

--cpu-player 2 will launch a game with two CPU agents, and takes no interactive input.

Display Modes

example_basic.py takes the following arguments to change display mode:

--render_mode="human" will render the game board visually using pygame. Player 1 plays red and goes first, while player 2 plays yellow.

When playing interactively, possible moves can be previewed by hovering the mouse over each square. To move a piece which is already placed, simply click on it.

--render_mode="text" will render a 3x3 board only showing the topmost pieces (pieces which are covered by others, or 'gobbled', are hidden):

TURN: 2, AGENT: player_1, ACTION: 51, POSITION: 6, PIECE: 3
       |       |       
  -    |   -   |   -3  
_______|_______|_______
       |       |       
  -    |   -   |   +2  
_______|_______|_______
       |       |       
  -    |   -   |   -   
       |       |       

--render_mode="text_full" will render three different 3x3 boards representing the small, medium and large pieces. This gives full information about pieces which are covered or 'gobbled' by other pieces. :

TURN: 3, AGENT: player_0, ACTION: 42, POSITION: 6, PIECE: 5
         SMALL                     MED                     LARGE           
       |       |                |       |                |       |       
  -    |   -   |   -       -    |   -   |   -       -    |   -   |   +5  
_______|_______|_______  _______|_______|_______  _______|_______|_______
       |       |                |       |                |       |       
  -    |   -   |   -2      -    |   -   |   -       -    |   -   |   -   
_______|_______|_______  _______|_______|_______  _______|_______|_______
       |       |                |       |                |       |       
  -    |   -   |   -       -    |   -   |   -       -    |   -   |   -6  
       |       |                |       |                |       |       

Testing

Testing can be done via pytest:

git clone https://github.com/elliottower/gobblet-rl.git
cd gobblet-rl
pytest