ACT-R is a cognitive architecture: a theory about how human cognition works. On the exterior, ACT-R looks like a programming language; however, its constructs reflect assumptions about human cognition. These assumptions are based on numerous facts derived from psychology experiments. Like a programming language, ACT-R is a framework: for different tasks (e., Tower of Hanoi, memory for text or for list of words, language comprehension, communication, aircraft controlling), researchers create models (aka programs) that are written in ACT-R and that, beside incorporating the ACT-R’s view of cognition, add their own assumptions about the particular task. These assumptions can be tested by comparing the results of the model with the results of people doing the same tasks.
By “results” we mean the traditional measures of cognitive psychology: time to perform the task, accuracy in the task, and, (more recently) neurological data such as those obtained from FMRI. One important feature of ACT-R that distinguishes it from other theories in the field is that it allows researchers to collect quantitative measures that can be directly compared with the quantitative measures obtained from human participants. ACT-R has been used successfully to create models in domains such as: learning and memory, problem solving and decision making, language and communication, perception and attention, cognitive development, or individual differences. Beside its applications in cognitive psychology, ACT-R has been used in human-computer interaction to produce user models that can assess different computer interfaces, education (cognitive tutoring systems) to “guess” the difficulties that students may have and provide focused help, computer-generated forces to provide cognitive agents that inhabit training environments, neuropsychology, to interpret FMRI data.
Some of the most successful applications, the Cognitive Tutors for Mathematics, are used in thousands of schools across the country. Such
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