There is mounting evidence that language comprehension involves the activation of mental imagery of the content of utterances (Barsalou, 1999;Bergen, Chang, & Narayan, 2004;Bergen, Narayan, & Feldman, 2003;Narayan, Bergen, & Weinberg, 2004;Richardson, Spivey, McRae, & Barsalou, 2003;Stanfield & Zwaan, 2001;Zwaan, Stanfield, & Yaxley, 2002). This imagery can have motor or perceptual content. Three main questions about the process remain under‐explored, however. First, are lexical associations with perception or motion sufficient to yield mental simulation, or is the integration of lexical semantics (...) into larger structures, like sentences, necessary? Second, what linguistic elements (e.g., verbs, nouns, etc.) trigger mental simulations? Third, how detailed are the visual simulations that are performed? A series of behavioral experiments address these questions, using a visual object categorization task to investigate whether up‐ or down‐related language selectively interferes with visual processing in the same part of the visual field (followingRichardson et al., 2003). The results demonstrate that either subject nouns or main verbs can trigger visual imagery, but only when used in literal sentences about real space—metaphorical language does not yield significant effects—which implies that it is the comprehension of the sentence as a whole and not simply lexical associations that yields imagery effects. These studies also show that the evoked imagery contains detail as to the part of the visual field where the described scene would take place. (shrink)

This article presents a computational model of the learning of diagnostic knowledge, based on observations of human operators engaged in real-world troubleshooting tasks. We present a model of problem solving and learning in which the reasoner introspects about its own performance on the problem-solving task, identifies what it needs to learn to improve its performance, formulates learning goals to acquire the required knowledge, and pursues its learning goals using multiple learning strategies. The model is implemented in a computer system which (...) provides a case study based on observations of troubleshooting operators and protocol analysis of the data gathered in the test area of an operational electronics manufacturing plant. The model not only addresses issues in human learning, but, in addition, is computationally justified as a uniform, extensible framework for multistrategy learning. (shrink)

Study on the philosophy of Sanskrit grammar in Vākyapadīya of Bhartr̥hari.