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-7393/95/S3.00 1995, Vol. 21, No . 2,449-468 Prior Knowledge and Functionally Relevant Features in Concept Learning Edward J. Wisniewski Northwestern University Empirical learning models have typically ...
to either enhance learning or impede it. The enhancement occurs when the hypothesis emphasizes category- relevant features , even if the hypothesis is in fact incorrect. A hypothesis that assigns high salience ...
Abstract: Due to its property of not requiring prior knowledge of the environment, reinforcement learning has significant potential for quantum control problems. In this work, we investigate ...
Abstract: Due to its property of not requiring prior knowledge of the environment, reinforcement learning has significant potential for quantum control problems. In this work, we investigate ...
knowledge . It copes with the ambiguity of user instructions by combining evidence from these sources. A dynamic bias manager generates candidate features (attribute values, functions , or relations) from which ...
of a new species unicept, on the basis of encounters with a single animal that exhibits novel biological features (75). The key point is that priming mechanisms themselves can have a prior function ...
| b is green) = 1/2; P(a is blue | b is green) = 1/2. The result is a failure to learn from experience. What we need is a prior probability function such that: P(a is green | b is green) > P(a is green ...
sets that capture the genomic and transcriptomic changes relevant to a specific condition, sample subtype, or biological pathway—this “ prior knowledge ” eventually accumulates in a growing number ...
to draw a concept map demonstrating their prior knowledge about mushrooms. The main experiment in the study consisted of three science-based learning activities which were related to the school curriculum ...
to the original content from where inference of a key concept was made, enabling users to verify OEA's interpretations. This feature could facilitate iterative learning of the algorithms as OEA reads more patient ...
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