Perceptual (Re)learning: A leverage point for human-centered computing

被引:19
|
作者
Hoffman, Robert R. [1 ]
Fiore, Stephen M.
机构
[1] Univ W Florida, Inst Human & Machine Cognit, Pensacola, FL 32514 USA
[2] Univ Cent Florida, Dept Philosophy, Orlando, FL 32816 USA
[3] Univ Cent Florida, Inst Simulat & Training, Orlando, FL 32816 USA
关键词
D O I
10.1109/MIS.2007.59
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Perceptual skill, which has been regarded as key to the advantage of experts, is acquired through deliberate acts of discrimination and differentiation combined with corrective feedback. Perceptual learning is not only about the perception of cues or evaluating the variables, but also include their meaningful integration. Any method for accelerating the achievement of expertise should be based on the ability to support the processes of learning and perceptual learning of dynamic cue configurations, including those that exist across multiple data types. Perceptual relearning of dynamical integral transmodal cue configurations, a concept that allow patterns previously learned and perceived in some way to be perceived in a new way, is a crucial element for intelligent systems. The perceptual learning process can be made possible by providing critical exemplars of targets.
引用
收藏
页码:79 / 83
页数:5
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