TY - GEN
T1 - Executive Function and Intelligent Goal-Directed Behavior
T2 - Workshops on AI4EA, F-IDE, CoSim-CPS, CIFMA 2022, Collocated with the 20th International Conference on Software Engineering and Formal Methods, SEFM 2022
AU - Pluck, Graham
AU - Cerone, Antonio
AU - Villagomez-Pacheco, David
N1 - Funding Information:
Work partly funded by Project SEDS2020004 “Analysis of cognitive properties of interactive systems using model checking”, Nazarbayev University, Kazakhstan (Award number: 240919FD3916), and a Chulalongkorn University, Faculty of Psychology Research Grant.
Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - The concept of executive function, as top-down control of processes, originated in computer science in the 1950s. However, it has since become an important concept in a range of human sciences, particularly for its explanatory power in psychology, education, and clinical neurosciences. Nevertheless, its use has been limited by vague definitions and confusion between the related conceptualizations of executive process and intelligence. Here we explore the concept of executive control in detail, drawing on psychology, neurology, and computer science/human-machine interaction. We explore both computationalist and embodied cognition approaches. We describe the core goal-directed and resource-limited features of executive control, its fractionation into components, and partial overlap with psychometric conceptions of intelligence. We also examine its associations with neurological systems beyond those usually linked to executive function (i.e., the frontal lobes). We propose that executive functions are ‘intelligent’, and can be defined by their goal-directedness. Furthermore, executive function tasks can be classified by their task goals into one of three types: Those that involve i) convergent, or ii) divergent thinking, or iii) not responding, such as in psychomotor response inhibition. Conventional intelligence tests measure only convergent thinking. The recognition of non-convergent executive functions allows the identification of executively controlled intelligent goal-directed behavior beyond that controlled by domain-general cognitive processes. This reconceptualization may benefit research in education, clinical and cognitive sciences, as well as the quest for artificial general intelligence.
AB - The concept of executive function, as top-down control of processes, originated in computer science in the 1950s. However, it has since become an important concept in a range of human sciences, particularly for its explanatory power in psychology, education, and clinical neurosciences. Nevertheless, its use has been limited by vague definitions and confusion between the related conceptualizations of executive process and intelligence. Here we explore the concept of executive control in detail, drawing on psychology, neurology, and computer science/human-machine interaction. We explore both computationalist and embodied cognition approaches. We describe the core goal-directed and resource-limited features of executive control, its fractionation into components, and partial overlap with psychometric conceptions of intelligence. We also examine its associations with neurological systems beyond those usually linked to executive function (i.e., the frontal lobes). We propose that executive functions are ‘intelligent’, and can be defined by their goal-directedness. Furthermore, executive function tasks can be classified by their task goals into one of three types: Those that involve i) convergent, or ii) divergent thinking, or iii) not responding, such as in psychomotor response inhibition. Conventional intelligence tests measure only convergent thinking. The recognition of non-convergent executive functions allows the identification of executively controlled intelligent goal-directed behavior beyond that controlled by domain-general cognitive processes. This reconceptualization may benefit research in education, clinical and cognitive sciences, as well as the quest for artificial general intelligence.
KW - Artificial intelligence
KW - Cognitive control
KW - Divergent thinking
KW - Executive function
KW - Frontal lobes
KW - Human-computer interaction
KW - Intelligence
KW - Neuroscience
UR - https://www.scopus.com/pages/publications/85151064358
UR - https://www.scopus.com/pages/publications/85151064358#tab=citedBy
U2 - 10.1007/978-3-031-26236-4_27
DO - 10.1007/978-3-031-26236-4_27
M3 - Conference contribution
AN - SCOPUS:85151064358
SN - 9783031262357
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 324
EP - 350
BT - Software Engineering and Formal Methods. SEFM 2022 Collocated Workshops - AI4EA, F-IDE, CoSim-CPS, CIFMA, Revised Selected Papers
A2 - Masci, Paolo
A2 - Bernardeschi, Cinzia
A2 - Palmieri, Maurizio
A2 - Graziani, Pierluigi
A2 - Koddenbrock, Mario
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 26 September 2022 through 30 September 2022
ER -