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Researchers at Binghamton University used Shannon entropy to develop a mathematical method that solves Wordle puzzles with a 99% success rate, prioritizing informative guesses over likely answers.
This article explains how incorporating Shannon entropy into reinforcement learning objectives creates more robust agents capable of handling unexpected or adversarial changes in rewards and dynamics.