This project aims to create a software capable of compute a promising solution in an acceptable amount of time in order to maximize the rewards for a given state of the Fishing Jigsaw game.
Fishing Jigsaw is a non-deterministic problem which is difficult to compute its best solution since in order to find it, the software would have to compute all possible states of the current board which is very expensive.
- The aim of the game is to fill all the spaces of the board.
- You will receive a reward depending on the numbers of attempts you make in order to fill the board, the less amount of attempts you make the better reward you will get.
- There are 6 types of figures you can get while playing the game, you will get one of them randomly each round.
- Every round you will be able to put the current figure in a valid position or skip it.
The approach used to solve the the game tree is a breadth-first search (BFS)-like algorithm that exhaustively explores all possible board configurations and figure placements to compute the optimal actions for solving the puzzle.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks!
- Fork the Project
- Create your Feature Branch
git checkout -b feature/AmazingFeature - Commit your Changes
git commit -m 'Add some AmazingFeature' - Push to the Branch
git push origin feature/AmazingFeature - Open a Pull Request
Distributed under the MIT License. See LICENSE for more information.
Discord - @aguunu 💖