Greedy Search
A heuristic search algorithm that selects the locally optimal solution at each step, reducing time complexity from exponential to polynomial. When applied to submodular function optimization, it carries a theoretical optimality guarantee of (1−1/e), approximately 63% of the global optimum.
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AI-generated text often exhibits uniform sentence length, formulaic transition words, and a lack of personal character, which is a statistical side effect of models choosing the highest-probability expressions (such as greedy search or low-temperature sampling).
Greedy search is a step-by-step decision strategy that, at each step, chooses the action that looks optimal under the current state without considering the impact on subsequent steps, and its drawback is that it cannot backtrack and easily gets stuck at a local optimum.
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AI-generated text often exhibits uniform sentence length, formulaic transition words, and a lack of personal character, which is a statistical side effect of models choosing the highest-probability expressions (such as greedy search or low-temperature sampling).
50%UnverifiedGreedy search is a step-by-step decision strategy that, at each step, chooses the action that looks optimal under the current state without considering the impact on subsequent steps, and its drawback is that it cannot backtrack and easily gets stuck at a local optimum.
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