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
相关论文
共 50 条
  • [31] 4 Perspectives in Human-Centered Machine Learning
    Guestrin, Carlos
    KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2019, : 3162 - 3162
  • [32] Visual Analytics for Human-Centered Machine Learning
    Andrienko, Natalia
    Andrienko, Gennady
    Adilova, Linara
    Wrobel, Stefan
    IEEE COMPUTER GRAPHICS AND APPLICATIONS, 2022, 42 (01) : 123 - 133
  • [33] Understanding people with human activities and social interactions for human-centered computing
    Choi, Sangil
    HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES, 2016, 6
  • [34] A human cyber-physical system for human-centered computing in seafaring
    Taylor N.C.
    Kruger K.
    Bekker A.
    Journal of Ambient Intelligence and Humanized Computing, 2023, 14 (06) : 7871 - 7884
  • [35] Towards Control Rooms as Human-Centered Pervasive Computing Environments
    Flegel, Nadine
    Poehler, Jonas
    Van Laerhoven, Kristof
    Mentler, Tilo
    SENSE, FEEL, DESIGN, INTERACT 2021, 2022, 13198 : 329 - 344
  • [36] Human-Centered Computing: A New Degree for Licklider's World
    Guzdial, Mark
    COMMUNICATIONS OF THE ACM, 2013, 56 (05) : 32 - 34
  • [37] Focus on People: Five Qestions from Human-Centered Computing
    Gatica-Perez, Daniel
    PROCEEDINGS OF THE 2022 INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, ICMI 2022, 2022, : 3 - 3
  • [38] Toward a theory of granular computing for human-centered information processing
    Bargiela, Andrzej
    Pedrycz, Witold
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2008, 16 (02) : 320 - 330
  • [39] Human-Centered Collaborative Robots With Deep Reinforcement Learning
    Ghadirzadeh, Ali
    Chen, Xi
    Yin, Wenjie
    Yi, Zhengrong
    Bjorkman, Marten
    Kragic, Danica
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (02) : 566 - 571
  • [40] Introduction to the Special Issue on Human-Centered Machine Learning
    Fiebrink, Rebecca
    Gillies, Marco
    ACM TRANSACTIONS ON INTERACTIVE INTELLIGENT SYSTEMS, 2018, 8 (02)