Evaluating Artificial Models of Cognition

Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such mo...

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Bibliographic Details
Main Author: Miłkowski Marcin
Format: Article
Language:English
Published: Sciendo 2015-03-01
Series:Studies in Logic, Grammar and Rhetoric
Subjects:
Online Access:https://doi.org/10.1515/slgr-2015-0003
Description
Summary:Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation of models does not depend on whether they target real biological agents or not; instead, the standards of evaluation depend on the use of models rather than on the reality of their targets. I discuss how models are validated depending on their use and argue that all-encompassing benchmarks for models may be well beyond reach.
ISSN:0860-150X
2199-6059