Introduction to Artificial Intelligence CS 438 Spring 2008

1. Introduction to Artificial IntelligenceCS 438 Spring 2008 • Today • AIMA, Ch. 6 • More Adversarial Search • Next Tuesday • AIMA, Ch. 13 • Reasoning with Uncertainty

2. SOE Open House • Schedule • EB 2029 • Activity • Man vs Machine Reversi • Class folder • Open House

3. Assignment 3: Game Playing • It Tourney Time!

4. Minimax Recap

5. α-β pruning • Strategy • Any path that is being expanded that is clearly worse than any known path can be abandoned early.

6. α is the value of the best (i.e., highest-value) choice found so far at any choice point along the path for max If v is worse than α, max will avoid it  prune that branch Define β similarly for min Why is it called α-β?

7. α-β pruning • α (alpha): Best choice for max • β (beta): Best choice for min if maxChoice >= β then prune if minChoice <= α then prune

8. α-β pruning example

9. α-β pruning example if maxChoice >= β then prune if minChoice <= α then prune

10. α-β pruning example if maxChoice >= β then prune if minChoice <= α then prune

11. α-β pruning example if maxChoice >= β then prune if minChoice <= α then prune

12. α-β pruning example if α >= β then prune if β <= α then prune

13. The α-β algorithm

14. The α-β algorithm

15. How many states can be avoided? • It depends on the order states are generated in • If the best moves for each player are generated first then significant pruning can occur • If the worst moves are generated first then NO pruning can occur