Population of Linear Experts: Knowledge Partitioning and Function Learning.
نویسندگان
چکیده
منابع مشابه
Population of linear experts: knowledge partitioning and function learning.
Knowledge partitioning is a theoretical construct holding that knowledge is not always integrated and homogeneous but may be separated into independent parcels containing mutually contradictory information. Knowledge partitioning has been observed in research on expertise, categorization, and function learning. This article presents a theory of function learning (the population of linear expert...
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The authors explored the phenomenon that knowledge is not always integrated and consistent but may be partitioned into independent parcels that may contain mutually contradictory information. In 4 experiments, using a function learning paradigm, a binary context variable was paired with the continuous stimulus variable of a to-be-learned function. In the first 2 experiments, when context predic...
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The relationship between function learning and other types of concept acquisition is far from well understood. Some models of function learning have used approaches that are very different from current models of categorization, while more recent function learning models have used exemplar representations, following the categorization literature. This paper describes two new models of function l...
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چکیده ندارد.
15 صفحه اولLearning with Knowledge from Multiple Experts
The use of domain knowledge in a learner can greatly improve the models it produces. However, high-quality expert knowledge is very difficult to obtain. Traditionally, researchers have assumed that knowledge comes from a single self-consistent source. A little-explored but often more feasible alternative is to use multiple weaker sources. In this paper we take a step in this direction by develo...
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ژورنال
عنوان ژورنال: Psychological Review
سال: 2004
ISSN: 1939-1471,0033-295X
DOI: 10.1037/0033-295x.111.4.1072