Adversarial Search: Minimax and Alpha–Beta Pruning
What changes when the world fights back, and an opponent picks every move to make you lose?
What this unit covers
Unit 4: Informed (Heuristic) Search and Adversarial Search
- 1 Heuristic Functions and Informed SearchAn okada rider who points "that side" is using a heuristic, a cheap guess at how far the goal still is. · 3 min
- 2 Greedy Best-First SearchFollow your nose: the most impatient way to use a hunch is to always expand the node that looks closest to the goal. · 3 min
- 3 A* SearchAdd the cost you've already paid to a guess of what's left, and you get the most famous search algorithm in AI. · 5 min
- 4 Admissible and Consistent HeuristicsWhen can a hunch be trusted? A* is only as trustworthy as the honesty of its guess. · 6 min
- 5 Adversarial Search: Minimax and Alpha–Beta PruningWhat changes when the world fights back, and an opponent picks every move to make you lose? · 4 min