Unit: Search Agents
Lesson: Adversarial Search
How Computers Think About Their Next Move
Inside the Minimax Algorithm
Cutting Corners to Win and Handling Chance
Play Tic-Tac-Toe Against AI!
Visualize Alpha-Beta Pruning (Optional)
Adversarial Search Quiz
Additional Resources (Optional)
It always provides the fastest solution
It requires special computer hardware
It only works with board games
It involves an opponent who is actively working against you
Maximize the number of moves
Maximize the time the opponent takes to decide
Maximize the number of pieces on the board
Maximize the score or utility value
To increase the difficulty level of the game
To eliminate branches of the game tree that won't affect the final decision
To ensure the computer always wins
To make the computer play more like a human
The first moves of the game
The hardest positions to evaluate
Final game states (win, lose, or draw)
Positions where the computer gets confused
Because the game tree is too large to explore completely
Because evaluation functions are more accurate than full searches
Because chess has no definite winning strategy
Because computers don't have enough memory for chess rules