This is actually a big issue with academic research related to bounded rationality. Although you could model it mathematically in another way, by far the most common is to use the rate-distortion approach. Rate distortion theory basically boils down to analyzing optimization problems of the form “minimize cost + (information-theoretic) entropy”. Problems of that form arise and are used for different reasons in fields including, e.g.: statistical mechanics, Bayesian statistics, anything in machine learning using softmax, large deviation theory, differential privacy, and, of course, bounded rationality and information theory.
However, since all these fields refer the same thing by different names, tools for handling problems in one field don’t get picked up by people working in another field. Either someone else rediscovers it later or someone has to have knowledge of multiple fields and see a connection. Sometimes the analysis done by one field isn’t useful in another due to different assumptions and research concerns, but that’s not obvious because you have to peel back a lot of layers of domain-specific jargon when reading the paper. Even though the math is very similar, reading a statistical mechanics paper written by a physicist is a real pain if you’re coming from an applied math / CS background, for example, because fields have their own notational conventions and refer to application scenarios that are meaningless to you and you need to figure out if that thing they reference is important to their development or not in the abstract.
It’s almost like reading House of Leaves. Here’s 30 pages with weird fonts describing the use of light in a non-existent movie and comparing it to both real movies and fake movies real people were supposedly involved in. Will it be relevant to the plot and thus require careful reading or can I skim this section? Maybe, but you won’t know unless you keep reading.