https://github.com/masaok/pacman-agent
Pacman Trainer: Classroom-Ready Deep Learning from Data to Deployment (ASEE Conference 2022 Paper Submission)
https://github.com/masaok/pacman-agent
python python3 tk tkinter
Last synced: 10 months ago
JSON representation
Pacman Trainer: Classroom-Ready Deep Learning from Data to Deployment (ASEE Conference 2022 Paper Submission)
- Host: GitHub
- URL: https://github.com/masaok/pacman-agent
- Owner: masaok
- Created: 2021-11-03T04:56:43.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2023-01-05T02:35:20.000Z (over 3 years ago)
- Last Synced: 2025-03-24T12:15:35.603Z (over 1 year ago)
- Topics: python, python3, tk, tkinter
- Language: Python
- Homepage:
- Size: 23 MB
- Stars: 2
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
## Pacman Trainer
### The final display with terminal debug output
## Prerequisites
- Python 3 (so far, it works with Python 3, but if there are problems, try Python 2)
## Environments Tested
### Windows 10 WSL2 Ubuntu (Build 19042.1288)
- Git Bash
- Python 3.8.10 (Window WSL2 Ubuntu)
- Python 3.9.8 ([See latest versions](https://www.python.org/downloads/))
- Python must be 3.9.x or earlier or [PyTorch will not work](https://pytorch.org/get-started/locally/#windows-python)
```
sudo apt update
sudo apt-get install python3-venv python3-tk
sudo apt-get install python3-tk
```
### MacOS 11.6 (Build 20G165)
- Python 3.9.4
```
brew install python-tk
```
## Quickstart
```
$ git clone git@github.com:masaok/pacman-agent.git
$ cd pacman-agent
$ python3 -m venv env
$ source env/Scripts/activate # Windows Git Bash only
$ source env/bin/activate # Mac / Linux only
$ pip install -r requirements.txt
$ python3 -u environment.py -h # Show command-line help
$ python3 -u environment.py # Run the app and show the GUI
```
```
$ deactivate # exit virtual environment
```
#### VcXsrv (X server for Windows to run GUI stuff)
Download and install VcXsrv from here: https://sourceforge.net/projects/vcxsrv/
When running it (it's called XLaunch in Windows), make sure to check this box:
Also, add [**this**](https://stackoverflow.com/a/61110604/10415969) to your `.bash_profile` and `source` it:
```
export DISPLAY=$(awk '/nameserver / {print $2; exit}' /etc/resolv.conf 2>/dev/null):0
export LIBGL_ALWAYS_INDIRECT=1
```
**Verify that VcXsrv is running correctly by testing Xcalc:**
Also, make this change in the code whereever `torch.load` is called:
https://stackoverflow.com/questions/56369030/runtimeerror-attempting-to-deserialize-object-on-a-cuda-device/62327502#62327502
**Run the real thing:**
`python3 -u environment.py`
## Components
- **PacmanAgent**: Contains all of the logic for the agent controlling Pacman
- **PacmanTrainer**: Contains the logic for training Pacman using Pytorch for deep imitation learning.
- **Environment**: Contains the game logic and is largely structured in the same way as the Wumpus World / Blindbot's environment
- A constructor, parameterized by the Pacman Trainer's array-of-strings maze representation, that initializes all of the maze variables, as follows:
- The maze structure, where walls are located, and thus what legal moves are available in any position.
- The sets and positions of all game actors (beginning with their provided starting positions), including:
- Pacman
- Ghosts
- Pellets
- Pacman's score (# of pellets eaten)
- Determining game-ending conditions (viz., Pacman getting eaten by a ghost or eating every pellet)
- Rendering the maze elements (in their basic array-of-strings format like in the Pacman Trainer) in terms of their graphical equivalents
- Actors in the environment take turns acting, so the environment determines what happens on every "tick" or turn of a running game:
- The PacmanAgent's chooseAction method is called with the current game state, and its action choice is enacted (if it's not a legal action, i.e., one that runs it into a wall, it does nothing that turn).
- If Pacman eats a pellet, it is removed from the board and the score is incremented
- If Pacman moves onto a ghost's tile, it dies and the game's over
- All ghosts make an action choice governed by a coin-flip: 10% of the time, it will choose randomly, and the other 90%, it will take a step that brings it closer to Pacman. You can use / adapt the Pathfinder class I gave in the BlindBot package to help with pathfinding or just do something basic like looking at the Manhattan distance between a ghost and Pacman and then choosing the action that minimizes it.
- **MazeUI**: Given a Tk "root window", draw a Tk Canvas on it and all the blocks, characters, and items that make up a maze
## Exercise
To view the accompanying exercise binding Pacman Trainer and Agent, see the EXERCISE.md instructions.