Simulating Explanatory Coexistence: Integrated, Synthetic, and Target-Dependent Reasoning

AbstractUnderstanding the cognitive structure of explanations— and the cognitive processes that assemble them— is a milestone for understanding how people learn and communicate. Recent research on explanatory coexistence suggests that people’s causal beliefs are less globally coherent than previously thought: people use seemingly-competing supernatural and biological causes to explain different aspects of the same phenomenon, or they assemble supernatural and biological causes into single, coherent explanations (Legare & Gelman, 2008; Legare & Shtulman, 2018; Shtulman & Lombrozo, 2016). This coexistence— and unexpected coherence— of diverse causal mechanisms poses interesting questions about the role of coherence and fragmentation in people’s mental models and explanations. This paper presents a computational model of explanatory coherence in the well-characterized domain of disease transmission, extending a previous cognitive model of explanation-based conceptual change (Friedman, Forbus, & Sherin, 2018). Our approach (1) retrieves diverse causal model fragments based on the phenomenon to explain, (2) assembles coherent causal models using relevance-directed abductive reasoning, and (3) selects explanatory paths that support within-explanation and within-scenario coherence. Our model simulates the three different types of explanatory coexistence detailed in the literature.


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