Abstraction and analogy-making in artificial intelligence.
Ann N Y Acad Sci
; 1505(1): 79-101, 2021 12.
Article
in En
| MEDLINE
| ID: mdl-34173249
ABSTRACT
Conceptual abstraction and analogy-making are key abilities underlying humans' abilities to learn, reason, and robustly adapt their knowledge to new domains. Despite a long history of research on constructing artificial intelligence (AI) systems with these abilities, no current AI system is anywhere close to a capability of forming humanlike abstractions or analogies. This paper reviews the advantages and limitations of several approaches toward this goal, including symbolic methods, deep learning, and probabilistic program induction. The paper concludes with several proposals for designing challenge tasks and evaluation measures in order to make quantifiable and generalizable progress in this area.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Psychomotor Performance
/
Semantics
/
Thinking
/
Pattern Recognition, Automated
/
Artificial Intelligence
Limits:
Humans
Language:
En
Journal:
Ann N Y Acad Sci
Year:
2021
Document type:
Article