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Artificial Intelligence — Complete Course Notes (BCA 7th Sem)

Comprehensive master lecture notes covering state space search, A* heuristic algorithms, Minimax, First Order Logic, Neural Networks, and NLP.

Artificial Intelligence · CACS401 · Semester 7

BCA Curriculum 2079

Unit 4•Unit 4 of 4

Unit 4: 3. Game Playing: Minimax and Alpha-Beta Pruning

In a two-player zero-sum game (e.g., Chess, Tic-Tac-Toe), MAX aims for the highest score while MIN aims to minimize MAX's score.

Alpha-Beta Pruning Parameters:

  • α (Alpha): The best (highest) value that MAX can guarantee at or above the current level.
  • β (Beta): The best (lowest) value that MIN can guarantee at or above the current level.
  • Pruning Condition: Prune remaining children of the node whenever α ≥ β. Alpha-Beta pruning achieves an optimal branching factor reduction from O(bm) to O(bm/2).

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