Resolving the associative learning paradox by category learning in pigeons.

ABSTRACT: A wealth of evidence indicates that humans can engage two types of mechanisms to solve category-learning tasks: declarative mechanisms, which involve forming and testing verbalizable decision rules, and associative mechanisms, which involve gradually linking stimuli to appropriate behavioral responses.^1,2,3 In contrast to declarative mechanisms, associative mechanisms have received surprisingly little attention in the broader category-learning literature. Although various forms of associatively driven artificial intelligence (AI) have matched-and even surpassed-humans' performance on several challenging problems,^3,4,5,6 associative learning is routinely dismissed as being too simple to power the impressive cognitive achievements of both humans and non-human species.^6,7,8,9 Here, we attempt to resolve this paradox by demonstrating that pigeons-which appear to rely solely on associative learning mechanisms in several tasks that promote declarative rule use by humans^3,10,11,12-succeed at learning a novel, highly demanding category structure that ought to hinder declarative rule use: the sectioned-rings task. Our findings highlight the power and flexibility that associative mechanisms afford in the realm of category learning.

SUBMITTER: Wasserman EA 

PROVIDER: S-EPMC10050111 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature