However, the epistemological approach differs from that of so-called "grounded cognition". We can summarise this difference as follows: while grounded cognition analyses the experience of a living system from the point of view of an observer, we adopt the point of view of the system itself, defined by the need to preserve the biological properties essential for its survival. Therefore, our proposal implies the idea that the system is self-referential, since it operates with the aim of being able to continue operating. The method is based on an algorithmic schema that we called Environment Generative Operator (EGO) and uses an object language developed for this purpose, that we called E-language. EGO simulates cognitive processes by manipulating E-language strings. Among all the feasible ones, an EGO model called "EGO-P" (Supplementary Material 2) was implemented and tested, achieving the expected objectives. Repositories 2 and 3, as all the others mentioned in the article, can be accessed via the corresponding link in the bibliography. E-language has various mathematical properties. Those useful for this work have been demonstrated and are available in Supplementary Material 1.

This paper argues that large language models have a valuable scientific role to play in serving as scientific models of a language. Linguistic study should not only be concerned with the cognitive processes behind linguistic competence, but also with language understood as an external, social entity. Once this is recognized, the value of large language models as scientific models becomes clear. This paper defends this position against a number of arguments to the effect that language models provide no linguistic insight. It also draws upon recent work in philosophy of science to show how large language models could serve as scientific models.