What strategy searches exhaustively through all options to solve a problem?

The answer focuses on the strategy known as searching a knowledge space. This approach involves systematically exploring all possible options or paths in order to find a viable solution to a problem. By examining every conceivable alternative, it ensures that no potential solution is overlooked, leading to a comprehensive understanding of the problem at hand.

This method is particularly important in scenarios where the problem space is complex and multifaceted, requiring a thorough exploration of all parameters and variables. Searching a knowledge space is pivotal in domains such as artificial intelligence and complex systems analysis, where exhaustive search can yield the optimal solution among numerous possibilities.

In contrast, the other strategies mentioned, such as recasting by analogy, decomposition, and means-end analysis, take different approaches. For instance, recasting by analogy focuses on finding similar problems that have been solved before and applying those solutions to a new problem, rather than examining every possible option. Decomposition breaks a problem down into smaller, more manageable subproblems, and means-end analysis involves setting subgoals to reach a final objective, both of which do not entail the exhaustive searching that characterizes searching a knowledge space.