The BACKTRACKING-SEARCH algorithm in Figure 5.3 has a very simple policy for what to do when a branch of the search fails: back up to the preceding variable and try a different value for it. This is called chronological-backtracking. It is also possible to go all the way to set of variable that caused failure. A. True B. False

[amp_mcq option1=”TRUE” option2=”nan” option3=”nan” option4=”nan” correct=”option1″]

The answer is False.

Chronological backtracking is a search strategy that backtracks to the previous decision point when a goal state cannot be reached from the current state. It is a depth-first search strategy that explores all possible branches of the search tree before backtracking.

In the BACKTRACKING-SEARCH algorithm in Figure 5.3, the algorithm backtracks to the preceding variable when a branch of the search fails. However, it is also possible to go all the way to the set of variables that caused failure. This is called goal-directed backtracking.

Goal-directed backtracking is a search strategy that backtracks to the previous decision point when a goal state cannot be reached from the current state. However, it does not explore all possible branches of the search tree before backtracking. Instead, it backtracks to the set of variables that caused failure and tries to find a solution from there.

Goal-directed backtracking is often more efficient than chronological backtracking because it does not explore all possible branches of the search tree. However, it can be more difficult to implement because it requires the algorithm to keep track of the set of variables that caused failure.

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