Subject
Computer Science
Topic
Artificial Intelligence
When a game tree is too large to search to the end, which function estimates how good a position is?
When a game tree is too large to search to the end, which function estimates how good a position is?
a)
Evaluation functionb)
Transposition functionc)
Utility of the rootd)
Successor functionExplanation
The search is cut off at some depth and an evaluation function scores the positions there.Related questions
In the figure, a complete binary game tree lists terminal values left-to-right as 3,12,8,2,4,6,14,5. If the root is MAX, what is its minimax value?During alpha-beta search, a MIN node obtains a value no greater than current alpha. What is safe?Two move orders examine the same fixed game tree with alpha-beta pruning. What remains unchanged?Which ordering usually improves alpha-beta pruning?With left-to-right alpha-beta search on a full binary tree whose leaves are 8,7,6,5,1,2,3,4, how many leaf evaluations are pruned?With left-to-right alpha-beta search on a full binary tree whose leaves are 4,3,2,1,8,7,6,5, how many leaf evaluations are pruned?A game contains chance events such as dice rolls. Which extension of minimax is appropriate?To which depth can alpha-beta pruning be applied?
