Using Wordle for Learning to Design and Compare Strategies
Wordle is a very popular word game that is owned by the New York Times. We can design parameterized strategies for solving Wordle, based on probabilistic, statistical, and information-theoretical information about the games. The strategies can handle a reasonably large family of Wordle-like games both systematically and dynamically, meaning that we do not rely on precomputations that may work for non-fixed games. More specifically, the answer set can be arbitrary, not confining to the current 2315 words. The answer words may include any specific number of letters (does not have to be five), and the set of symbols that form the words does not have to be limited to only the English alphabet. Exploring possible strategies for solving the Wordle-like games offers an attractive learning challenges for students who are learning to design computer games. This paper will provide the results of using two families of parameterized strategies to solve the current Wordle, using the simulator that abides by the hard-mode rules as the baseline. The baseline simulator used an average of 4.078 guesses to find the 2315 answers, and needed more than six trials to solve the game 1.77% of the time. The best performing strategy of ours used an average of 3.674 guesses to find the 2315 answers, and failed 0.65% of the time.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
On Optimal Strategies for Wordle and General Guessing Games
The recent popularity of Wordle has revived interest in guessing games. We develop a general method for finding optimal strategies for guessing games while avoiding an exhaustive search. Our main contributions are severa…
Reinforcement Learning Methods for Wordle: A POMDP/Adaptive Control Approach
In this paper we address the solution of the popular Wordle puzzle, using new reinforcement learning methods, which apply more generally to adaptive control of dynamic systems and to classes of Partially Observable Marko…
reinforcement-learningReinforcement LearningReinforcement Learning (RL)Finding the optimal human strategy for Wordle using maximum correct letter probabilities and reinforcement learning
Wordle is an online word puzzle game that gained viral popularity in January 2022. The goal is to guess a hidden five letter word. After each guess, the player gains information about whether the letters they guessed are…
Selecting Seed Words for Wordle using Character Statistics
Wordle, a word guessing game rose to global popularity in the January of 2022. The goal of the game is to guess a five-letter English word within six tries. Each try provides the player with hints by means of colour chan…
Wordle: A Microcosm of Life. Luck, Skill, Cheating, Loyalty, and Influence!
Wordle is a popular, online word game offered by the New York Times (nytimes.com). Currently there are some 2 million players of the English version worldwide. Players have 6 attempts to guess the daily word (target word…