Abstract
<p>Risky options often differ not only in outcomes and probabilities, but also in the cognitive demands required to evaluate them. Yet most theories of risky choice either ignore complexity or treat it as a static feature of the option, modeled as a utility discount or with heteroscedastic errors. We propose a process-level framework that explains how complexity shapes both choice and response time within an evidence-accumulation architecture. The framework assumes that complexity reduces the signal-to-noise ratio of evidence accumulation, making evaluation slower and choices less consistent, and that decision makers partly adapt to these processing constraints by adjusting their decision strategies. These mechanisms can explain how complexity reduces choice consistency and how it shifts preferences toward simpler options.We evaluated this framework in three preregistered experiments that manipulated complexity in structurally distinct ways: through the number of outcomes, arithmetic expressions of outcomes, and compound probabilities. Across studies, complexity made choices slower and less consistent. When both options were complex, these effects were best explained by reduced signal-to-noise ratios and partially compensatory increases in decision thresholds. When options differed in complexity, preferences for simpler options were best explained by an initial bias toward simplicity combined with a drift-rate adjustment during accumulation. The compound-probability manipulation, however, marked a boundary condition: different forms of complexity can change the representations that evidence accumulation operates on. Together, these findings advance a dynamic account of risky choice in which complexity shapes preference construction by changing both the rate at which decision evidence accumulates and the strategies used to evaluate the options.</p>