An AI that uses an adversarial minimax search with alpha-beta purning to determine the best subsequent move. The program also supports player vs. player games.
usage: halma <b-size> <t-limit> [<h-player>]
The final project for this course was structured around creating this adversarial AI so that the teams in class could compete in one final tournament on the last day of class.
Our AI worked its way through 4 games of this single-elimination tournament to win first place.
- The move-finding method is under the assumption that pieces cannot re-enter friendly goals or leave enemy goals even during a jump chain.
- Computation is currently fixed to a ply-depth of 3 rather than using dynamic depth.
- Turn time exhaustion will simply break the recursion with its current max.
- Peter Huettl - ph289@nau.edu
- Garrison Smith - gts35@nau.edu