What is rote learning in the Shopper computer program?

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In the context of the Shopper computer program, developed by Anthony Oettinger in 1952, rote learning refers to the program's ability to store and recall specific information it encountered during its operations.1

As the program navigated a simulated mall of eight shops to locate items, it would memorize a portion of the inventory stocked in each shop it visited. When tasked with finding an item it had previously located, the program used this stored memory to navigate directly to the correct shop, rather than searching at random. This process of simple memorization—retaining specific facts for future use—is defined as rote learning in the history of machine learning.1