I searched on Google, Wikipedia, Google scholar, and more, but I could not find the origin of Autoencoders. Perhaps it's one of those concepts that evolved very gradually, and it's impossible to trace back a clear starting point, but still I would like to find some kind of summary of the main steps of their development.
The chapter about autoencoders in Ian Goodfellow, Yoshua Bengio and Aaron Courville's Deep Learning book says:
The idea of autoencoders has been part of the historical landscape of neuralnetworks for decades (LeCun, 1987; Bourlard and Kamp, 1988; Hinton and Zemel,1994). Traditionally, autoencoders were used for dimensionality reduction or feature learning.
This presentation by Pascal Vincent says:
Denoising using classical autoencoders was actually introduced much earlier (LeCun, 1987; Gallinari et al., 1987), as an alternative to Hopfield networks (Hopfield, 1982).
This seems to imply that "classical autoencoders" existed before that: LeCun and Gallinari used them but did not invent them. I see no trace of "classical autoencoders" earlier than 1987.