Game Theory: Optimal Decisions in Adversarial Search
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Game Theory: Optimal Decisions in Adversarial Search

Explore the concepts of game theory, including optimal decisions in games, alpha-beta tree search, and heuristic search. Learn how to make strategic moves in adversarial situations.

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@SupplePelican

Questions and Answers

What is the primary reason for implementing quiescence search in a chess evaluation function?

To avoid counting material in positions with favourable captures

What is the main disadvantage of forward pruning in game tree search?

It may prune a better or best move

What is the purpose of singular extension in dealing with the horizon effect?

To avoid considering moves that are not clearly better

What is the primary benefit of using alpha-beta pruning in game tree search?

<p>It reduces the number of nodes to be searched</p> Signup and view all the answers

What is the main goal of implementing a reasonable cutoff test in game tree search?

<p>To reduce the number of nodes to be searched</p> Signup and view all the answers

In the context of game tree search, what is the primary purpose of a transposition table?

<p>To avoid revisiting the same nodes</p> Signup and view all the answers

What is the main challenge in implementing alpha-beta pruning in game tree search?

<p>Dealing with the exponential growth of the search tree</p> Signup and view all the answers

What is the primary advantage of using beam search in game tree search?

<p>It reduces the number of nodes to be searched</p> Signup and view all the answers

What is the main limitation of using a simple evaluation function that only counts material in chess?

<p>It does not account for quiescent positions</p> Signup and view all the answers

What is the primary goal of implementing minimax search in game tree search?

<p>To find the optimal move in a given position</p> Signup and view all the answers

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