What are the key factors that influence the effectiveness of genetic algorithms in generating crosswords by vocabulary?
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Genetic algorithms' effectiveness in generating crosswords by vocabulary is influenced by several key factors. These include the algorithm's ability to reach local optima and find successful words, as seen in American-style crossword puzzles with a GA + WoAC approach, showing a 20% improvement in reaching local optima and a 6% increase in successful words over baseline GAs . Additionally, the structure of chromosome data plays a crucial role, with experiments showing that the genetic algorithm can outperform existing non-deterministic algorithms but falls short compared to deterministic algorithms in identifying characteristics in text databases . Furthermore, the complexity of crossword puzzle variants like go-words necessitates a probabilistic approach due to the vast search space, making genetic algorithms a suitable choice for solving such NP-complete problems .
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5 Citations | Not addressed in the paper. |
Open access•Journal Article 11 Citations | The key factors influencing the effectiveness of genetic algorithms in generating crosswords by vocabulary include the improved strategy based on niche technical and multi-father body variable rank hybrid. |
01 Mar 1993 7 Citations | Key factors influencing genetic algorithms in generating crosswords by vocabulary are population size, generations number, genetic material shared, and mutation frequency, crucial for efficient solutions in crossword construction. |
29 Citations | The key factors influencing genetic algorithms in generating equifrequent groups of words are the chromosome data structures and the algorithm's ability to produce superior results compared to non-deterministic methods. |
27 Jul 2015 5 Citations | The effectiveness of genetic algorithms in generating crosswords is influenced by the integration of Wisdom of Artificial Crowds (WoAC) aggregation method, leading to improved performance in finding successful words. |
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