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Published on: August 25, 2023
Social learning and exploration-exploitation dilemma in decision-making
Gota Morishita1, Shinsuke Suzuki1,2,3
1Centre for Brain, Mind and Markets, The University of Melbourne, Parkville, VIC, Australia.
Humans often prioritize learning from reliable partners over exploratory ones, influencing social learning strategies. This neurocomputational approach explores the exploration-exploitation dilemma in social contexts.
Area of Science:
- Neuroscience
- Cognitive Science
- Computational Neuroscience
Background:
- Social learning is crucial for adaptation.
- Neural mechanisms for social learning are known, particularly in the prefrontal cortex.
- The interplay between social learning and the exploration-exploitation trade-off is less understood.
Purpose of the Study:
- To review the neurocomputational principles of social learning.
- To examine how the exploration-exploitation dilemma influences social learning.
- To investigate source selection strategies in social learning.
Main Methods:
- Literature review of neurocomputational principles.
- Analysis of the exploration-exploitation trade-off in social contexts.
- Discussion of strategic social behaviors like free-riding and conformity.
Main Results:
- Social environments shape the exploration-exploitation trade-off.
- Humans exhibit a reliability-seeking bias in source selection.
- Preference for learning from consistent, exploitation-oriented partners over exploratory ones.
Conclusions:
- Current paradigms confound social cues like competence and predictability.
- A computational framework is needed to isolate drivers of adaptive social decision-making.
- Understanding reliability bias is key to adaptive social learning.
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