Elements of cognition for general intelligence

Christian Balkenius; Birger Johansson; Trond A. Tjøstheim

doi:10.1007/978-3-031-33469-6_2

Elements of cognition for general intelligence

Christian Balkenius, Birger Johansson, Trond A. Tjøstheim

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

Abstract

What can artificial intelligence learn from the cognitive sciences? We review some fundamental aspects of how human cognition works and relate it to different brain structures and their function. A central theme is that cognition is very different from how it is envisioned in classical artificial intelligence which offers a novel path toward intelligent systems that in many ways is both simpler and more attainable. We also argue that artificial intelligent systems takes more than a single silver bullet. It requires a large number of interacting subsystem that are coupled to both the body and to the environment. We argue for an approach to artificial general intelligence based on a faithful reproduction of known brain processes in a system-level model that incorporates a large number of components modelled after the human brain.

Original language	English
Title of host publication	Artificial General Intelligence
Subtitle of host publication	16th International Conference, AGI 2023, Stockholm, Sweden, June 16–19, 2023, Proceedings
Editors/authors	Patrick Hammer, Marjan Alirezaie , Claes Strannegård
Place of Publication	Cham
Publisher	Springer
Pages	11-20
Number of pages	10
Volume	13921
ISBN (Electronic)	978-3-031-33469-6
ISBN (Print)	978-3-031-33468-9
DOIs	https://doi.org/10.1007/978-3-031-33469-6_2
Publication status	Published - 2023

Publication series

Name	Lecture Notes in Computer Science
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Name	Lecture Notes in Artificial Intelligence
Volume	13921
ISSN (Print)	2945-9141
ISSN (Electronic)	2945-9133

Subject classification (UKÄ)

Computer Sciences
Other Computer and Information Science
Other Engineering and Technologies
Information Systems, Social aspects (including Human Aspects of ICT)

Access to Document

10.1007/978-3-031-33469-6_2

https://rdcu.be/dcUVX

Cite this

Balkenius, C., Johansson, B., & Tjøstheim, T. A. (2023). Elements of cognition for general intelligence. In P. Hammer, M. Alirezaie , & C. Strannegård (Eds.), Artificial General Intelligence: 16th International Conference, AGI 2023, Stockholm, Sweden, June 16–19, 2023, Proceedings (Vol. 13921, pp. 11-20). (Lecture Notes in Computer Science), (Lecture Notes in Artificial Intelligence; Vol. 13921). Springer. https://doi.org/10.1007/978-3-031-33469-6_2

Balkenius, Christian ; Johansson, Birger ; Tjøstheim, Trond A. / Elements of cognition for general intelligence. Artificial General Intelligence: 16th International Conference, AGI 2023, Stockholm, Sweden, June 16–19, 2023, Proceedings. editor / Patrick Hammer ; Marjan Alirezaie ; Claes Strannegård . Vol. 13921 Cham : Springer, 2023. pp. 11-20 (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence).

@inproceedings{5a9232ba44e74a8d8a1d936aca60d650,

title = "Elements of cognition for general intelligence",

abstract = "What can artificial intelligence learn from the cognitive sciences? We review some fundamental aspects of how human cognition works and relate it to different brain structures and their function. A central theme is that cognition is very different from how it is envisioned in classical artificial intelligence which offers a novel path toward intelligent systems that in many ways is both simpler and more attainable. We also argue that artificial intelligent systems takes more than a single silver bullet. It requires a large number of interacting subsystem that are coupled to both the body and to the environment. We argue for an approach to artificial general intelligence based on a faithful reproduction of known brain processes in a system-level model that incorporates a large number of components modelled after the human brain.",

author = "Christian Balkenius and Birger Johansson and Tj{\o}stheim, \{Trond A.\}",

year = "2023",

doi = "10.1007/978-3-031-33469-6\_2",

language = "English",

isbn = "978-3-031-33468-9",

volume = "13921",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "11--20",

editor = "Hammer, \{Patrick \} and \{Alirezaie \}, Marjan and \{Stranneg{\aa}rd \}, Claes",

booktitle = "Artificial General Intelligence",

address = "Germany",

}

Balkenius, C , Johansson, B & Tjøstheim, TA 2023, Elements of cognition for general intelligence. in P Hammer, M Alirezaie & C Strannegård (eds), Artificial General Intelligence: 16th International Conference, AGI 2023, Stockholm, Sweden, June 16–19, 2023, Proceedings. vol. 13921, Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, vol. 13921, Springer, Cham, pp. 11-20. https://doi.org/10.1007/978-3-031-33469-6_2

Elements of cognition for general intelligence. / Balkenius, Christian ; Johansson, Birger ; Tjøstheim, Trond A.
Artificial General Intelligence: 16th International Conference, AGI 2023, Stockholm, Sweden, June 16–19, 2023, Proceedings. ed. / Patrick Hammer; Marjan Alirezaie ; Claes Strannegård . Vol. 13921 Cham: Springer, 2023. p. 11-20 (Lecture Notes in Computer Science), (Lecture Notes in Artificial Intelligence; Vol. 13921).

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

TY - GEN

T1 - Elements of cognition for general intelligence

AU - Balkenius, Christian

AU - Johansson, Birger

AU - Tjøstheim, Trond A.

PY - 2023

Y1 - 2023

N2 - What can artificial intelligence learn from the cognitive sciences? We review some fundamental aspects of how human cognition works and relate it to different brain structures and their function. A central theme is that cognition is very different from how it is envisioned in classical artificial intelligence which offers a novel path toward intelligent systems that in many ways is both simpler and more attainable. We also argue that artificial intelligent systems takes more than a single silver bullet. It requires a large number of interacting subsystem that are coupled to both the body and to the environment. We argue for an approach to artificial general intelligence based on a faithful reproduction of known brain processes in a system-level model that incorporates a large number of components modelled after the human brain.

AB - What can artificial intelligence learn from the cognitive sciences? We review some fundamental aspects of how human cognition works and relate it to different brain structures and their function. A central theme is that cognition is very different from how it is envisioned in classical artificial intelligence which offers a novel path toward intelligent systems that in many ways is both simpler and more attainable. We also argue that artificial intelligent systems takes more than a single silver bullet. It requires a large number of interacting subsystem that are coupled to both the body and to the environment. We argue for an approach to artificial general intelligence based on a faithful reproduction of known brain processes in a system-level model that incorporates a large number of components modelled after the human brain.

UR - https://www.scopus.com/pages/publications/85163321229

U2 - 10.1007/978-3-031-33469-6_2

DO - 10.1007/978-3-031-33469-6_2

M3 - Paper in conference proceeding

SN - 978-3-031-33468-9

VL - 13921

T3 - Lecture Notes in Computer Science

SP - 11

EP - 20

BT - Artificial General Intelligence

A2 - Hammer, Patrick

A2 - Alirezaie , Marjan

A2 - Strannegård , Claes

PB - Springer

CY - Cham

ER -

Balkenius C , Johansson B , Tjøstheim TA. Elements of cognition for general intelligence. In Hammer P, Alirezaie M, Strannegård C, editors, Artificial General Intelligence: 16th International Conference, AGI 2023, Stockholm, Sweden, June 16–19, 2023, Proceedings. Vol. 13921. Cham: Springer. 2023. p. 11-20. (Lecture Notes in Computer Science). (Lecture Notes in Artificial Intelligence). doi: 10.1007/978-3-031-33469-6_2

Elements of cognition for general intelligence

Abstract

Publication series

Subject classification (UKÄ)

Access to Document

Other files and links

Fingerprint

Cognitive modeling

Lund University Cognitive Robotics Lab

Cite this

Elements of cognition for general intelligence

Abstract

Publication series

Subject classification (UKÄ)

Access to Document

Other files and links

Fingerprint

Projects

Cognitive modeling

Infrastructure

Lund University Cognitive Robotics Lab

Cite this