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Causal reasoning from almost first principles
A formal theory of causal reasoning is presented that encompasses both Pearl’s approach to causality and several key formalisms of nonmonotonic...
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The development of human causal learning and reasoning
Causal understanding is a defining characteristic of human cognition. Like many animals, human children learn to control their bodily movements and...
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Causal reasoning with causal graphs in educational technology research
Researchers tasked with understanding the effects of educational technology innovations face the challenge of providing evidence of causality. Given...
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Causal reasoning in typical computer vision tasks
Deep learning has revolutionized the field of artificial intelligence. Based on the statistical correlations uncovered by deep learning-based...
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Causal Reasoning Meets Visual Representation Learning: A Prospective Study
Visual representation learning is ubiquitous in various real-world applications, including visual comprehension, video understanding, multi-modal...
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A Logical Approach to Doxastic Causal Reasoning
Belief revision and causality play an important role in many applications, typically, in the study of database update mechanisms and data dependence....
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Causal Reasoning over Probabilistic Uncertainty
A system deployed in the real world will need to handle uncertainty in its observations and interventions. For this, we present an approach to...
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Benchmarking causal reasoning algorithms for gene expression-based compound mechanism of action analysis
BackgroundElucidating compound mechanism of action (MoA) is beneficial to drug discovery, but in practice often represents a significant challenge....
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An Inferential Theory of Causal Reasoning
We present a general formalism of causal reasoning that encompasses both Pearl’s approach to causality and a number of key systems of nonmonotonic...
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Inferential Pluralism in Causal Reasoning from Randomized Experiments
Causal pluralism can be defended not only in respect to causal concepts and methodological guidelines, but also at the finer-grained level of causal...
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A Primer to Causal Reasoning About a Complex World
This open access book is about causal thinking and the use of causal language, with a focus on introducing philosophical ideas about causation to...
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Leveraging on non-causal reasoning techniques for enhancing the cognitive management of highly automated vehicles
Highly Automated Vehicles (HAVs) are expected to improve the performance of terrestrial transportations by providing safe and efficient travel...
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Understanding unforeseen production downtimes in manufacturing processes using log data-driven causal reasoning
In discrete manufacturing, the knowledge about causal relationships makes it possible to avoid unforeseen production downtimes by identifying their...
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Multi-Criteria Decision Making (MCDM) with Causal Reasoning for AI/ML Applications – A Survey
Multi-criteria decision making (MCDM) refers to making the best possible decision out of different alternatives based on factors which can sometimes...
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Evidential reasoning rule for environmental governance cost prediction with considering causal relationship and data reliability
Environmental governance cost prediction can avoid blind investment and waste of resources and achieve effective cost planning for sustainable...
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Students Do Not Always Mean What We Think They Mean: A Questioning Strategy to Elicit the Reasoning Behind Unexpected Causal Patterns in Student System Models
An ability to engage in system thinking is necessary to understand complex problems. While many pre-college students use system modeling tools, there...
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Causal Deep Q Networks
Deep Q Networks (DQN) have shown remarkable success in various reinforcement learning tasks. However, their reliance on associative learning often...
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Generalizable inductive relation prediction with causal subgraph
Inductive relation prediction is an important learning task for knowledge graph reasoning that aims to infer new facts from existing ones. Previous...
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Granular Nested Causal Complexes
Causal reasoning occupies a central position in human reasoning. In many ways, causality is granular. This is true for: perception, commonsense...