Resumen

ALMEIDA, Saulo  y  SILVA, Paulo Caetano da. The importance of machine learning in affect studies. Psic., Saúde & Doenças [online]. 2023, vol.24, n.3, pp.1059-1072.  Epub 31-Dic-2023. ISSN 1645-0086.  https://doi.org/10.15309/23psd240322.

Machine learning is a field of Artificial Intelligence in which a system can modify a behavior, autonomously, based on its own experience, using logical rules that modify the performance of a task or make the most appropriate decision. for the context. One of its main challenges is to think about how a machine can learn to deal with affects or their correlates in the interaction with human beings or other agents. For this, this work seeks to understand what has been produced in an association between the areas of affection and machine learning, through a systematic literature review. After the filters applied, 22 articles dealing with the research topics are discussed. In general, the works deal directly with human affectivity or it appears as an element linked to general concepts, as is the case of studies on engagement. The works discussed stand out for the use of machine learning in the reading and analysis of data taken from the results of diagnostic tests or lexical networks, associated with equipment for analyzing brain activity, highlighting the electroencephalogram (EEG), or even the use of robots, chatbots or electronic games.

Palabras clave : Machine learning; Affections; Artificial intelligence; Psychological assessment; Psychology.

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