associative memory

Terms from Artificial Intelligence: humans at the heart of algorithms

An assocative memory is one which tries to learn the relationship between an input and an output so that when given an unseen input it can allocate an appropriate output. In some case the output is very different from the output, known as an heteroassociative memory, for example, where an image is associated with a class. In others the memory can be used as an autoencoder where the input and output are identical – this form of auto-associative memory initially does not seem useful, however it may be used where the input is in some way incomplete or noisy and the memory recreates a full or noise-free image.

Used in Chap. 6: pages 74, 80

Different kinds of associative memory