Shannon Entropy: The Science Behind Candy Rush’s Randomness
Shannon entropy, defined by Claude Shannon in 1948, quantifies uncertainty per symbol in a message or system using the formula H = -Σ p(i)log₂p(i), where p(i) is the probability of symbol i. This measure captures the average information content—each time we observe an unlikely event, we gain more information. Beyond information theory, entropy reflects the …
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