NOTE: The AI element is currently under development.
Implements the negamax recursive algorithm to minimise the possible loss for a worst-case scenario.
The computer player wishes to maximise its score, future moves/board states are therefore scored from both players perspectives. Simply, it maximises the score for itself and minimises it for the opponent.
Utilises Alpha-Beta Pruning to narrow the exploration window by taking into account previously explored moves.
The number of nodes evaluated by the negamax search is therefore decreased. Evaluation for a move is stopped when there has been >= 1 other possibility found that proves the move to be worse than a previously explored move.
We can further narrow the exploration window following Alpha-Beta Pruning by exploring columns closer to the centre and moving outwards.
This is as moves closer to the central column are involved in more alignments.
Our board state can be stored as a bit map.
(TODO: Complete)
- Anticipation of losing moves
- Iterative deepening
- The implementation of a transposition table for the caching of moves
V1.0 Released with GUI and CLI Interfaces
