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Causal Reasoning with Forces [PDF]
Frontiers in Human Neuroscience, 2015 Causal composition allows people to generate new causal relations by combining existing causal knowledge. We introduce a new computational model of such reasoning, the force theory, which holds that people compose causal relations by simulating the ...
Phillip eWolff, Aron K Barbey
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Causal reasoning with mental models [PDF]
Frontiers in Human Neuroscience, 2014 This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A
Sangeet eKhemlani +2 more
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Causal reasoning without mechanism. [PDF]
PLoS ONE, 2022 Unobservable mechanisms that tie causes to their effects generate observable events. How can one make inferences about hidden causal structures? This paper introduces the domain-matching heuristic to explain how humans perform causal reasoning when ...
Selma Dündar-Coecke +2 more
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Benchmarking causal reasoning algorithms for gene expression-based compound mechanism of action analysis [PDF]
BMC Bioinformatics, 2023 Background Elucidating compound mechanism of action (MoA) is beneficial to drug discovery, but in practice often represents a significant challenge. Causal Reasoning approaches aim to address this situation by inferring dysregulated signalling proteins ...
Layla Hosseini-Gerami +6 more
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A Magic Act in Causal Reasoning: Making Markov Violations Disappear [PDF]
EntropyA desirable property of any theory of causal reasoning is to explain not only why people make causal reasoning errors but also when they make them. The mutation sampler is a rational process model of human causal reasoning that yields normatively correct
Bob Rehder
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Probabilistic causal reasoning under time pressure. [PDF]
PLoS ONEWhile causal reasoning is a core facet of our cognitive abilities, its time-course has not received proper attention. As the duration of reasoning might prove crucial in understanding the underlying cognitive processes, we asked participants in two ...
Ivar R Kolvoort +4 more
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Causal reasoning in rats' behaviour systems [PDF]
Royal Society Open Science, 2018 Conceiving of stimuli and responses as causes and effects, and assuming that rats acquire representational models of causal relations from Pavlovian procedures, previous work by causal model theory proponents attempted to train rat subjects to represent ...
Robert Ian Bowers, William Timberlake
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Evaluation of causal reasoning for large language models in contextualized clinical scenarios of laboratory test interpretation [PDF]
npj Digital MedicineThis study evaluates causal reasoning in large language models (LLMs) using 99 clinically grounded laboratory test scenarios mapped to Pearl’s Ladder of Causation: association, intervention, and counterfactual reasoning.
Balu Bhasuran +5 more
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Consistency in causal reasoning for large language models in scenarios of HIV antiretroviral treatment, drug interactions, and side effects [PDF]
npj Digital MedicineWe aimed at evaluating the consistency in causal reasoning capabilities of large language models (LLMs) in disease-specific contexts, across the three levels of the causal ladder—associational, interventional, and counterfactual.
Mattia Prosperi +13 more
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Improving students' causal reasoning skills with the computer modelling [PDF]
Fanāvarī-i āmūzish, 2023 Background and Objectives: Computer modelling helps a lot in learning comprehensive scientific concepts, including the causal mechanisms of phenomena, which is challenging for novice learners. Despite the many studies that have been published to show the
M. Jahanifar, M. Hormozi Nejad
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