Umfang:
1 Online-Ressource (xxiv, 359 Seiten)
,
Illustrationen, Diagramme
ISBN:
9781668491911
Serie:
Advances in computational intelligence and robotics (ACIR)
Inhalt:
"Establishing the means to improve performance in healthy, clinical, and military populations has long been a focus of study in the psychological and brain sciences. However, a major obstacle to this goal is generating individualized performance phenotypes that allow for the design of interventions that are tailored to the specific needs of the individual. Recent developments in artificial intelligence (AI) have qualified for the development of precision approaches that consider individual differences, allowing, for example, the establishment of individualized training, preparation, and recuperation programs optimal for an individual's cognitive and biological phenotype. Corollary developments in AI have proven that combining domain expertise and stakeholder insights can considerably improve AI's quality, performance, and dependability in the psychology and brain sciences.Recent Developments in Machine and Human Intelligence studies original empirical work, literature reviews, and methodological papers that establish and validate precision AI methods for human performance optimization with a focus on modeling individual differences via state-of-the-art computational methods and investigating how domain expertise and human judgment can improve the performance of AI methods. The topics are crafted in such a way as to cover all the areas of artificial and human intelligence that require AI for further development. This book contains algorithms and techniques that are explained with the help of developed source code and encompasses the readiness and needs for advancements in managing yet another pandemic in the future. It is designed for academicians, scientists, research scholars, professors, graduates, undergraduates, and students."
Anmerkung:
"Premier reference source"-- Cover
Weitere Ausg.:
Erscheint auch als Druck-Ausgabe ISBN 978-1-6684-9189-8
Sprache:
Englisch
Schlagwort(e):
Künstliche Intelligenz
;
Deep learning
;
Maschinelles Lernen
;
Erkenntnistheorie
DOI:
10.4018/978-1-6684-9189-8
URL:
Volltext
(URL des Erstveröffentlichers)
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