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Published on: June 3, 2013
Similarity and rules: distinct? Exhaustive? Empirically distinguishable?
1Department of Psychology, University of Warwick, Coventry, UK. u.hahn@warwick.ac.uk
Cognition
|April 29, 1998
Summary
This study clarifies the difference between rule-based and similarity-based cognition by focusing on how information is matched. It suggests combining both approaches is key for future research in artificial intelligence and cognitive science.
Area of Science:
- Cognitive Science
- Artificial Intelligence
- Psychology
Background:
- The distinction between rule-based and similarity-based cognitive processes is crucial but theoretically challenging.
- Existing research has not clearly linked theoretical distinctions to empirical evidence.
Purpose of the Study:
- To propose a core distinction between rule- and similarity-based processes based on representational matching.
- To provide a framework for evaluating psychological and AI literature on cognitive processes.
Main Methods:
- Defined a core distinction based on representational matching mechanisms.
- Analyzed existing psychological and AI literature to assess evidence for rule- and similarity-based processes.
Main Results:
- Many psychological findings are less conclusive than previously assumed.
- Converging evidence may offer a more persuasive basis for distinction.
- AI literature indicates a growing trend towards hybrid rule- and similarity-based approaches.
Conclusions:
- The proposed core distinction clarifies the rule/similarity debate in cognitive science.
- Future empirical work should focus on hybrid models combining rules and similarity.
- This framework aids in assessing the psychological and AI literature.
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