You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
Unfortunately this project's code is not on github. That is because the original repository became so full of training data and generated images that it was too large to be hosted. However, you can still download the code for my VAE and my augmentation script via the round button at the top right.
This project was made for hack_state at Mississippi State University. Originally, we had much more ambitious goals than just a script. My other team members were to work on a front end where you could simply take a picture of your tiles, and be given back an arrangement of them. Due to overestimations in our teams ability and time constraints, we settled for something much less at the hackathon. After the event, I extracted the script that I had wrote, and tweaked it to be standalone with simple text input. This is the current state of the project.
The project uses a combination of a prefix tree (or "trie") and a depth first search. A dictionary of valid words is contained in the project folder, and a prefix tree is built with that dictionary. When given an input of letters, the program finds all possible words to make using the letters at any given point, and tries to place one on the board in a legal way.
The program follows a "longest first" heuristic, in which longer words are prioritized over smaller words in order to get rid of as many tiles as possible. If not all tiles can be used, the configuration which uses the most tiles is displayed to the user.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
We built this project completely from scratch. No external machine learning or game engine libraries were used. We wrote our own game engine for checkers in python, and we wrote all the logic for the agent to learn, store data, and make decisions using Python. Again, more details can be found in the project report.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.
You can find the code for this project, and all my other projects via the round button at the top right of this popup window.