<p>Model comparison and context-dependent feature reweighting.</p>

Bars show differences in expected log predictive density () relative to the best-performing model (multi-feature policy). The multi-feature policy outperformed all single-feature and alternative heuristic models, indicating that behavior is best captured by a combination of task-relevant features.

Asterisks (*) denote features that were included in the multi-feature policy. <b>(B)</b> Posterior estimates (mean 95% credible intervals) from the unified hierarchical model showing main effects and condition-dependent modulation of decision features on foraging behavior (logit scale). Positive values indicate increased probability of foraging. Avoidance contexts selectively modulated feature weights, including reduced sensitivity to and increased influence of -values.