For this university module, a Minimax Algorithm was developed to attempt to play chess and beat a human player. for this, a scoring system that valued each piece as well as the position a piece was in was used to help the AI judge what a valuable move would be.
For the final rendition, Negamax was used, to make use of Alpha-Beta pruning and increase the speed of the AI's decisions. As well as this, common openings were added.
This AI, while basic, is very capable of winning games or stalemating if drawn into a corner.
For the final rendition, Negamax was used, to make use of Alpha-Beta pruning and increase the speed of the AI's decisions. As well as this, common openings were added.
This AI, while basic, is very capable of winning games or stalemating if drawn into a corner.
