Reprint

Socio-Cognitive and Affective Computing

Edited by
September 2018
254 pages
  • ISBN978-3-03897-198-6 (Paperback)
  • ISBN978-3-03897-199-3 (PDF)

This is a Reprint of the Special Issue Socio-Cognitive and Affective Computing that was published in

Biology & Life Sciences
Chemistry & Materials Science
Computer Science & Mathematics
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary
Social cognition focuses on how people process, store, and apply information about other people and social situations. It focuses on the role that cognitive processes play in social interactions. On the other hand, the term cognitive computing is generally used to refer to new hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. In this sense, it is a type of computing with the goal of discovering more accurate models of how the human brain/mind senses, reasons, and responds to stimuli.Socio-Cognitive Computing should be understood as a set of theoretical interdisciplinary frameworks, methodologies, methods and hardware/software tools to model how the human brain mediates social interactions. In addition, Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects, a fundamental aspect of socio-cognitive neuroscience. It is an interdisciplinary field spanning computer science, electrical engineering, psychology, and cognitive science.Physiological Computing is a category of technology in which electrophysiological data recorded directly from human activity are used to interface with a computing device. This technology becomes even more relevant when computing can be integrated pervasively in everyday life environments. Thus, Socio-Cognitive and Affective Computing systems should be able to adapt their behavior according to the Physiological Computing paradigm.This book integrates proposals from researchers who use signals from the brain and/or body to infer people's intentions and psychological state in smart computing systems. The design of this kind of systems combines knowledge and methods of ubiquitous and pervasive computing, as well as physiological data measurement and processing, with those of socio-cognitive and affective computing.
Format
  • Paperback
License and Copyright
© 2019 by the authors; CC BY license
Keywords
human–computer interaction; ambient intelligence; interruption factor; belief–desire–intention agents; perceptual computing; Type-2 fuzzy inference system; 3D display; visual fatigue; electroencephalogram (EEG); causative factor; small world network; six degrees of separation; map reduce; community detection; modularity; normalize mutual information; distress estimation; wearable; heart rate variability; photoplethysmography; frequent subgraph mining; parallel, algorithm; constraint satisfaction problem; Spark; affective computing; emotion recognition; emotion representation models; emotion mapping; Ekman’s six basic emotions; Pleasure-Arousal-Dominance model; affective computing; Bayesian neural network; Multiple Label Learning; transfer learning; long short-term memory networks; behavior modelling; intelligent environments; activity recognition; affective computing; human–computer interaction; social computing; human aspects of software engineering; affective software engineering; individualization; dynamic path planning; driving habits; personalized performance evaluation; machine learning; enhanced feature engineering; parallel processing of model; feature optimization; eMLEE; eFES; overfitting; underfitting; optimum fitting; ambient intelligence; human-computer interaction; internet of things; smart homes; intelligent tutoring systems; affect-aware tutoring; human–computer interaction; etiquette strategy; user frustration; n/a