Pac-man AI Framework written in c++17.
This framework can be used to evaluate AI Planning algorithms. All you need to do is write your pac-man implementation and provide a layout file.
More importantly, this framework can be used to learn AI Planning algorithms by writing their implementation in C++.
This project is inspired by The Pac-Man Projects.
To build the project you need to install the following dependencies:
- Compiler that supports C++17
- CMake
- clang-tidy (for linter)
- Qt5 (for display)
- GTest (for building unit tests)
- spdlog (for logging)
- yaml-cpp (for configs)
The easiest way for you is to use the docker container to build and run the pacman-ai-cpp application. After installing docker on your system, you can run the following command to build the docker image:
docker build --tag pacman-ai-cpp:latest --file Dockerfile .
To build the software, start your container at the root of the project by executing ./setup.sh.
It supports both Linux and Mac OS.
If you are using the docker container on Mac OS, you must install xquartz before executing ./setup.sh. It is required to run GUI applications on containers.
To run in a container shell, you can execute the following:
./main/pacman -l ./layout_files/medium_5_ghosts.lay -p random
If you modify config or layout files, you have to execute cmake .. to copy them to the build directory.
To build the application, from the root directory, execute:
mkdir build && cd build
cmake ..
make
This framework comes with Random Movement Pac-man see random_pacman_impl.cpp. It simply checks the state of the world, get possible actions (not blocked by walls) and randomly chooses one.
To execute the example after building it, you can simply execute:
./main/pacman -l ./layout_files/medium_5_ghosts.lay -p random
random is your pac-man algorithm's name.
You can follow the examples to write your own pac-man implementation.
If you're interested in understanding the details you can read the blog post here.
Please report issues if you found bugs or raise a Pull Request.