In computer simulations, this information theory-based method outperformed traditional strategies
Millions of people try to uncover a hidden five-letter word in the New York Times’ popular puzzle game, Wordle.
In a recent breakthrough, researchers at Binghamton University developed a method to solve Wordle with a 99 percent of success rate.
The new strategy is based on “Shannon entropy”, a concept from information that is used to measure and reduce uncertainty.
Under this strategy, the focus is choosing words that are the most informative instead of guessing words with the highest probability of being the correct answer. The goal is to maximize the reduction of uncertainty, leading to eliminating the largest number of incorrect possibilities.
According to Congyu "Peter" Wu, a faculty member at the Thomas J. Watson College of Engineering, "Let's say you're at a certain guess. The previous guesses will eliminate a whole bunch of options, and based on the remaining options, guessing some words will send you into a trajectory where information gain is speedier.”
Players use a separate script or program that analyzes the color-coded feedback (Grey, Yellow, Green) from each guess to recommend the next word that will provide the most useful information.
"A subtle but important insight from the paper is that a guess doesn't have to be the most likely answer; it simply has to be informative," said Donald Stephens, a doctoral student at Binghamton University.
"By applying Shannon entropy, the objective shifts to maximizing the expected reduction in uncertainty rather than the probability of being right. In practice, this approach can lead to solving the puzzle in fewer guesses."
In computer simulations, this information theory-based method outperformed traditional strategies by securing 99 percent success rate compared to 90 percent.