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Poster Session A: Tuesday, August 12, 1:30 – 4:30 pm, de Brug & E‑Hall

Computational Modeling of Heuristic and Base-rate Integration in Reasoning

Jérémie Beucler¹, Zoe Purcell¹, Lucie Charles, Kobe Desender², Wim De Neys; ¹Université Paris Cité, ²KU Leuven

Presenter: Jérémie Beucler

Base-rate neglect, a key example of biased reasoning, is often attributed to the interplay between intuitive and deliberative processes in dual-process theories. Yet these explanations remain largely verbal and theoretically underspecified. Participants (N = 151) performed a novel, continuous base-rate neglect task where base-rate information and stereotype-driven heuristic strength (quantified using language models) were parametrically manipulated. Clustering analyses revealed three distinct reasoning profiles: stereotype-driven, base-rate-driven, and balanced. A biased drift diffusion model (DDM), in which weighted stereotype and base-rate information jointly determine the drift rate, captured individual differences and reproduced key empirical patterns in accuracy, confidence, and response time. Results show that confidence and reaction time reflect the same underlying evidence signal as choice, revealing how information is integrated during reasoning. Importantly, the model predicts that biased individuals do not benefit from increased deliberation, as they fail to integrate the logical information in the first place. This work advances the computational modeling of reasoning and offers a theoretical framework for understanding how individuals integrate conflicting information.

Topic Area: Reward, Value & Social Decision Making

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