Quantitative abstraction theory
A quantitative theory of abstraction is presented. The central feature of this is a growth formula defining the number of abstractions which may be formed by an individual agent in a given context. Implications of the theory for artificial intelligence and cognitive psychology are explored. Its possible applications to the issue of implicit v. explicit learning are also discussed.
History
Publication status
- Published
Journal
Journal of Artificial Intelligence and Simulation of BehaviourISSN
1476-3036Issue
3Volume
1Page range
281-290Department affiliated with
- Informatics Publications
Full text available
- Yes
Peer reviewed?
- Yes