Animals often exhibit extremely rapid action changes in context-switching environments. This study hypothesized that, compared to the expected outcome, an unexpected outcome leads to distinctly different action-selection strategies to guide rapid adaptation. We designed novel behavioral measures differentiating between trial-by-trial dynamics after expected and unexpected events. In various reversal learning data with different rodent species and task complexities, conventional learning models failed to replicate the choice behavior following an unexpected outcome. This discrepancy was resolved by the proposed model with two different decision variables contingent on outcome expectation: the support-stay and conflict-shift bias. Electrophysiological data analyses revealed that striatal neurons encode our model's key variables. Furthermore, the inactivation of striatal direct and indirect pathways neutralizes the effect of past expected and unexpected outcomes, respectively, on the action-selection strategy following an unexpected outcome. Our study suggests new roles of the striatum in arbitrating between different action selection strategies for few-shot adaptation.