The project aimed to create an efficient Wordle solver using Python, focusing on optimizing strategies to solve the word puzzle game with minimal guesses.
- Preparation: Filtered a Scrabble word list to include only 5-letter words.
- Simulation: Implemented a Python-based Wordle game to evaluate guesses and outcomes.
- Optimization: Employed frequency analysis and a letter score method, along with a hybrid approach combining both techniques.
- Simulation: Tested over 5000 Wordle game sessions.
- Findings:
- The hybrid approach was most effective, achieving a higher win rate.
- The average number of guesses required per game was significantly reduced using the hybrid method compared to standalone frequency analysis or letter score methods.
- Numerical Outcomes:
- Hybrid Approach: Achieved a win rate of 98.68% with an average of 3.88 guesses per game.
- Frequency Analysis and Letter Score Methods: Showed lower efficiency, with win rates and average guesses not surpassing the hybrid's performance.
Please view the Jupyter Notebook for detailed code and methodology.