[3][2] Figure 1 highlights the links between perceived knowledge, memory, and acquired experiences that are formed based on “familiar patterns” [2] between new and old information.
[5] According to Gobet et al. and Smith et al., cognitive templates, or better known as schemas, form when chunks adapt based on recurring environmental patterns and structures.
For example, during the learning phase of the chess simulations, the program incrementally acquires chunks and templates by scanning a large database of positions taken from master-level games.
[3] In the case of chess experiments, perception is equated with eye movements (which are approximately correspondent to attention), which are directed by chunks held in memory and heuristics .
[8][10] Time-related variables are commonly used in CHREST and its subsequent simulations, such as the main limiting factor of visual short-term memory being restricted.
[9][10] Additionally, extensive research conducted by Woollett and Maguire revealed that through acquiring expertise, such as in the case of London's taxi drivers, “structural plasticity in the hippocampus” [12][13] is developed, creating “permanent changes in the brain” [13] such as the expansion of the posterior hippocampal region relative to the average population.
[12][14] This change is achieved through memorisation and navigation of complicated routes and maps of London's urban area,[13] leading to a rigid pattern of cognitive chunks that results in resistance to sudden modifications, as well as the development of “practised habits”.
[12][14] The plasticity of the information processing centre in the brain leads to potential “blind spots” [13] when faced with situations that require visualisation external of preexisting patterns.
[14][13][12] The chess domain has long been a standardised testing protocol for studies involving perception, psychology, cognition, and human and artificial intelligence.
[4] In the algorithm's learning phase, chunks and templates from databases containing moves, positions, and strategies from grandmaster and expert level games are gradually fed and synthesised as knowledge.
[4] In the domain of perception, simulations of eye movement during the initial 5 seconds of illustrating a chess position, as well as recognition of templates and chunks have been completed using CHREST.
[22] Retschitzki et al. suggest the decline of the skill level of the older players as a consequence of reaching and passing their peak,[22] and explicit comparison to a younger age group was complicated due to “prior learning and past experiences”,[23] also referred to as “crystallised intelligence”.