# Social learning and exploration–exploitation dilemma in decision-making

## TL;DR

This paper explores how people balance learning from others with maximizing rewards in decision-making.

## Contribution

It introduces a new framework for understanding biases in selecting social learning sources.

## Key findings

- Humans prefer reliable, exploitation-oriented partners over exploratory ones for social learning.
- Current paradigms confound social cues like competence and predictability.
- A computational framework is proposed to isolate drivers of adaptive social decisions.

## Abstract

This mini review examines the neurocomputational principles of social learning through the lens of the exploration–exploitation dilemma. While the neural mechanisms of learning from others—mediated by distinct signals in the ventromedial and lateral prefrontal cortices—are well established, less is known about how these mechanisms interact with the fundamental trade-off between gathering information (“exploration”) and maximizing rewards (“exploitation”). We discuss how social environments shape this trade-off, leading to strategic behaviors such as informational free-riding or conformity. A central focus of this review is the issue of source selection: how agents decide whom to observe. We present recent evidence suggesting that, contrary to the predictions of optimal information-seeking theories, humans often exhibit a “reliability-seeking” bias, preferring to learn from consistent, exploitation-oriented partners rather than highly exploratory ones. We conclude by discussing the limitations of current paradigms, specifically the inherent confounding of social cues such as competence and predictability, and outline a computational framework for isolating the specific drivers of adaptive social decision-making.