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Published on: June 30, 2020
Value generalization, not normalization, drives learning in structure-based grouped contexts
Bingsong Zhao1, Jing Gan1, Shengyuan Wang1
1Department of Psychology, Guangdong Provincial Key Laboratory of Social Cognitive Neuroscience and Mental Health, Sun Yat-sen University.
People learn values in structured contexts, not just individual items. This study shows value generalization, not just normalization, explains how we learn values in groups, even when it leads to overestimating less valuable items.
Area of Science:
- Cognitive Science
- Neuroscience
- Decision Science
Background:
- Value learning typically studied at the individual object level.
- Dominant account, value normalization, suggests context-relative encoding, leading to contrastive biases.
- Empirical support for normalization is limited to proximity-based grouping.
Purpose of the Study:
- Investigate context-dependent value learning in structured environments.
- Test value generalization as an alternative to value normalization.
- Examine how conceptual or relational structure influences value learning.
Main Methods:
- Five experiments using modified multi-armed bandit tasks.
- Participants inferred group structure through trial-and-error learning.
- Computational modeling compared value generalization and normalization models.
Main Results:
- Participants overestimated values of below-average items in high-mean groups.
- Assimilative bias persisted across various grouping types and reward framing.
- Value generalization models significantly outperformed normalization and item-level models.
Conclusions:
- Findings challenge the dominance of value normalization in structured environments.
- Value generalization is identified as an efficient, albeit imperfect, strategy for context-dependent value learning.
- Value learning in natural environments is influenced by inferred group structures.
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