General cognitive principles for learning structure in time and space

Coevolution of learning and data-acquisition mechanisms: a model for cognitive evolution

“…We have just explained how acquiring streams of data and processing them using the basic principles of associative learning results in a process that is virtually the same as our general model for learning structure [10,11]. We demonstrated this with a specific example in which an animal acquires data along its path of movement, and suggested that this is likely to be adaptive because such data streams include useful things to learn, even though they are not immediately related to food.…”

“…To develop such abilities, humans and animals must learn the statistical regularities in the data, which in turn will enable them to learn how the data are structured, both spatially and temporally. As mentioned in §1, in our previous work, we suggested that during learning, additional processes are at work that compare data sequences, segment them based on commonalities and update their weight and link structure in memory representation [10,11]. We also described in more detail how such processes can facilitate advanced cognitive abilities such as language acquisition or theory of mind and what evidence is currently available to support the existence of such processes.…”

“…We have argued elsewhere that by recursively applying these principles of comparison of data streams within a restricted learning window, further associations can be detected and hierarchical structure can be constructed in the data representation [10,11,20]. We also suggested that, as part of this process, similarity can be identified at the level of link structure, which facilitates generalization and the use of context.…”

“…It is not enough for a dog to acquire all the sentences uttered by its owners and search for commonalities. It must also have the appropriate rates of weight increase and decrease (and their possible modification by state or social cues) that would result in a sensible segmentation of sentences into words, and a correct representation of their structural relationships [11]. Thus, in terms of our model, at least some cognitive differences across species (as well as individual differences within a species [50]) may be based on specific coevolved combinations of data-acquisition and learning parameters.…”

“…We believe that in order to model the evolution of more complex learning or cognitive mechanisms, it is necessary to make some additional assumptions about how they work and how their components can gradually be modified by natural selection. Over the past few years, we have developed a model of learning and cognitive development and explored its ability to explain a range of phenomena [10,11]. Here, we take an evolutionary approach to examine the model's plausibility and its potential use for the study of cognitive evolution.…”