Computationalism

Artificial Intelligence (AI) is a domain of computer science focused on devices that are able to take some level of agency in achieving novel goals. Beyond that detail, the scope of AI is disputed, in part because “novel goals” is a moving target … as once-unimaginable feats become routine. Commonly mentioned aspects include abilities to collect relevant information about the environment, draw inferences based on that information, and apply those inferences flexibly.

Computational Cognition is an approach to research learning that focuses on the development of computational models fitted to empirical evidence and attentive to human experience. Critically, Computational Cognition does not assert or assume that the mind is an information-processing system; rather, the orienting premise is that technologies of computation afford useful means to study human cognition (including sub-phenomena, such as intention, motivation, emotion, and perception) by using complex, dynamic models.

Machine Learning encompasses all efforts and strategies to structure and program machines to improve their performances on specific tasks. In these applications, “learning” is usually defined in operational rather than cognitive terms – that is, in terms of measurable improvements in performance that are due to changes in the machine’s structure, programs, or data. Many strategies are under development, employing different computer architectures and a range of logics.

Cognitivism is explicitly developed around the metaphor “brain as computer.” It thus focuses on how information is acquired, processed, and organized. Learning is seen in terms of integration of new information into existing structures through processes of internal codification.