Week 5
The creation of the groups were on this week. Group members: Kho Ryan Anggada and Nicolas.
links to their blog:
Nicolas – http://2101704520nicolas.blog.binusian.org/intelligent-systems/
Ryan – http://2101704672ryan.blog.binusian.org/intelligent-systems/
Week 6
We decided to look for a topic on this week. After discussing with the team, we decided to choose Othello/Reversi because it is a classic game that has perfect information and finite. For the AI, we decided to use Minimax Alpha-Beta Pruning as it is the perfect algorithm for a solved, deterministic, perfect information and finite game.
Week 7
This week, we decided to take an in depth look at Othello because we need to learn how to play well in order to create good heuristics.
Week 8
In this week, we looked around on how to create the game on the internet. We used a website called inventwithpython to learn how to code the Othello game.
Week 9
This week, we started coding the game itself. We decided to split the files so that it is neat and tidy. We started on the base game first as it is the most important thing as without the base game, we cannot implement the UI and AI.
Week 10
Once the base game is finished, we created the UI using pygame. This makes the game more attractive and easier to test.
Week 11
This week, we implement the Minimax Alpha-Beta Pruning. First, we needed to create the heuristics. We decided to use location to determine the value of the board. Corners are worth a lot as they cannot be flipped, Tiles beside the corner are worth negative points as it gives the opponent a chance to take the corner. We decided to be the min player, playing black, while the AI get to play the max player, playing white.
Week 12
After playing with the AI a bit, we decided that a difficulty setting would be a good addition as the AI can be too hard sometimes. So, we decided to add easy, which searches the game with depth of 2, medium which searches the game with depth of 3 and hard which searches the game with depth of 4.
Week 13
Presentation week.