Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICTAI.2009.65
Title: Probabilistic neural logic network learning: Taking cues from neuro-cognitive processes
Authors: Chia, H.W.K. 
Tan, C.L. 
Sung, S.Y.
Issue Date: 2009
Source: Chia, H.W.K., Tan, C.L., Sung, S.Y. (2009). Probabilistic neural logic network learning: Taking cues from neuro-cognitive processes. Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI : 698-702. ScholarBank@NUS Repository. https://doi.org/10.1109/ICTAI.2009.65
Abstract: This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive learning. The "selectionist" nature of human decision making indicates the use of an evolutionary paradigm for composing rudimentary neural network units, while the "constructivist" component takes the form of neural weight training during the learning process. We explore the possibility of amalgamating these two ideas into a neural learning system for the discovery of meaningful rules in the context of pattern discovery in data. © 2009 IEEE.
Source Title: Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
URI: http://scholarbank.nus.edu.sg/handle/10635/41161
ISBN: 9781424456192
ISSN: 10823409
DOI: 10.1109/ICTAI.2009.65
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