A Gomoku AI With Minimax, Alpha-Beta Pruning, and Pattern-Based Evaluation The hard AI does a 4-ply minimax search with alpha-beta pruning. A 15×15 board has 225 cells, so naive minimax at depth 4 would visit 225^4 ≈ 2.5 billion positions. Pruning + restricting moves to cells within radius 2 of existing stones cuts this to a few thousand. Combined with a pattern-based evaluator that scores open

A Gomoku AI With Minimax, Alpha-Beta Pruning, and Pattern-Based Evaluation
SEN LLC·Dev.to··1 min read
D
Continue reading on Dev.to
This article was sourced from Dev.to's RSS feed. Visit the original for the complete story.