Instance‐based Learning
A General Model of Repeated Binary Choice
Bibliographic Data
| ID | 12166318 |
|---|---|
| Authors | Tomás Lejarraga (0000-0001-6135-2243, Decision Sciences (United States), corresponding author), Dutt (0000-0002-2151-8314, Decision Sciences (United States)), Cleotilde González (0000-0002-6244-2918, Decision Sciences (United States)) |
| Year | 2010 |
| Volume | 25 |
| Issue | 2 |
| Pages | 143-153 |
| Publication date | 2010-12-02 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Behavioral Decision Making (JOURNAL) |
| Journal identifiers | ISSN: 0894-3257 • E-ISSN: 1099-0771 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/bdm.722 |
| OpenAlex | W2058346590 |
| Language | EN |
| Citations received | 10 |
| References cited | 21 |
A common practice in cognitive modeling is to develop new models specific to each particular task. We question this approach and draw on an existing theory, instance‐based learning theory (IBLT), to explain learning behavior in three different choice tasks. The same instance‐based learning model generalizes accurately to choices in a repeated binary choice task, in a probability learning task, and in a repeated binary choice task within a changing environment. We assert that, although the three tasks are different, the source of learning is equivalent and therefore, the cognitive process elicited should be captured by one single model. This evidence supports previous findings that instance‐based learning is a robust learning process that is triggered in a wide range of tasks from the simple repeated choice tasks to the most dynamic decision making tasks. Copyright © 2010 John Wiley & Sons, Ltd
Binary number · Cognition · Cognitive model · Cognitive psychology · Machine learning · Multi-task learning · Process (computing · Range (aeronautics · Simple (philosophy · Task (project management · Bayesian Modeling and Causal Inference · Cognitive Science and Mapping · Computer Science · Decision-Making and Behavioral Economics · Mathematics · Psychology · Artificial Intelligence
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| Unique citing works | 10 |
|---|---|
| Citations per year | 0,77 |
| Citation span | 2013 - 2026 (14) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 9 |