Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search
University Question with Answer
Adversarial search - Artificial Intelligence and Machine Learning
Explain perfect decisions in game playing
University
Questions with Answers
May 2003
Q.1 Explain perfect decisions in game playing? Give example. (Refer
sections 5.1 and 5.2) [16]
Dec.
2003
Q.2 Explain minimax algorithms and how it works for game of
tic-tac-toe. (Refer section 5.11 )[8]
Dec.
2004
Q.3 Explain minimax search procedure with example upto 3rd
ply. (Refer section 5.11 ) [8]
Q.4 Describe alpha-beta
pruning using example. Show game tree upto
3rdply.(Refer
sections 5.11 and 5.12)[16]
May
2009
Q.5 Explain minimax procedure for game playing. Is this DFS or BFS?
How it can be modified to be used by a program playing three-four player game? (Refer
section 5.11 ) [8]
Q.6 How minimax procedure
can be modifed to play multiplayer game?
(Refer section 5.11)[8]
May
2010
Q.7 Describe minimax
procedure and alpha-beta pruning. (Refer sections 5.11 and 5.12) [16]
Dec.
2010
Q.8 Explain alpha-beta pruning algorithm with example. (Refer
section 5.12)
[10]
May
2017
Q.9 Explain Minimax
algorithm in detail. (Refer section 5.11)[16]
Q.10 Explain Alpha-Beta
pruning and Alpha-Beta algorithm.
(Refer section 5.12)[16]
May
2019
Artificial Intelligence and Machine Learning: Unit I(e): Adversarial search : Tag: : Adversarial search - Artificial Intelligence and Machine Learning - University Question with Answer
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Artificial Intelligence and Machine Learning
CS3491 4th Semester CSE/ECE Dept | 2021 Regulation | 4th Semester CSE/ECE Dept 2021 Regulation