Black:
Human
AI (Type A; try to get many disks)
AI (Type B; try to own corner positions)
AI (Type C; try to own corner positions carefully)
AI (Type D; Prioritize number of moves)
AI (Type E; Prioritize number of moves and positions)
AI (Type M-128; Monte Carlo Tree Search with 128 iterations)
AI (Type M-256; Monte Carlo Tree Search with 256 iterations)
AI (Type M-512; Monte Carlo Tree Search with 512 iterations)
AI (Type M-1024; Monte Carlo Tree Search with 1024 iterations)
AI (Type M-2048; Monte Carlo Tree Search with 2048 iterations)
AI (Type M-4096; Monte Carlo Tree Search with 4096 iterations)
AI (Type M-1024/old; Monte Carlo Tree Search with 1024 iterations)
AI (Type PM-100/m; Primitive Monte Carlo with 100 iterations for each move)
AI (Type PM-200/m; Primitive Monte Carlo with 200 iterations for each move)
AI (Type PM-1024/e; Primitive Monte Carlo with 1024 iterations divided for each move)
White:
Human
AI (Type A; try to get many disks)
AI (Type B; try to own corner positions)
AI (Type C; try to own corner positions carefully)
AI (Type D; Prioritize number of moves)
AI (Type E; Prioritize number of moves and positions)
AI (Type M-128; Monte Carlo Tree Search with 128 iterations)
AI (Type M-256; Monte Carlo Tree Search with 256 iterations)
AI (Type M-512; Monte Carlo Tree Search with 512 iterations)
AI (Type M-1024; Monte Carlo Tree Search with 1024 iterations)
AI (Type M-2048; Monte Carlo Tree Search with 2048 iterations)
AI (Type M-4096; Monte Carlo Tree Search with 4096 iterations)
AI (Type M-1024/old; Monte Carlo Tree Search with 1024 iterations)
AI (Type PM-100/m; Primitive Monte Carlo with 100 iterations for each move)
AI (Type PM-200/m; Primitive Monte Carlo with 200 iterations for each move)
AI (Type PM-1024/e; Primitive Monte Carlo with 1024 iterations divided for each move)
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