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The target of many studies in the health sciences is the discovery of cause-effect relationships among observed variables of interest, for example: treatments, exposures, preconditions, and outcomes. Causal modeling and causal discovery are central to medical science. In order to algorithmically consider causal relations, the relations must be placed into a representation that supports manipulation...
Causal reasoning occupies a central position in human reasoning. In order to algorithmically consider causal relations, the relations must be placed into a representation that supports manipulation. The most widespread causal representation is directed acyclic graphs (DAGs). However, DAGs are severely limited in what portion of the every day world they can represent. Both possible causal relationships...
Causal complexes are groupings of smaller causal relations that make up a large grained causal object. Usually, commonsense reasoning is more successful in reasoning about a few large-grained events than many fine-grained events. However, the larger-grained causal objects are necessarily more imprecise as some of their constituent components. Causality is imprecisely granular in many ways. Knowledge...
Humor is everywhere, as long as you are willing to see it, both accidental and intentional. Computers have evolved from simple calculating machines to playing chess, controlling air and space flights, and talking to humans. They are increasingly used to informally gather information from humans using human language. The paper mentions that will a computer ever understand humor as well as we do? Some...
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