An empirical study of knowledge representation and learning within conceptual spaces for intelligent agents
Lee, Ickjai, and Portier, Bayani (2007) An empirical study of knowledge representation and learning within conceptual spaces for intelligent agents. In: Proceedings of 6th IEEE/ACIS International Conference on Computer and Information Science, pp. 463-468. From: ICES 2007 6th IEEE/ACIS International Conference on Computer and Information Science, 11-13 July 2007, Melbourne, Australia.
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This paper investigates the practicality and effectiveness of conceptual spaces as a framework for knowledge representation. We empirically compares and contrasts two popular quantitative lazy learning systems (nearest neighbor learning and prototype learning) within conceptual spaces and mere multidimensional feature spaces. Experimental results demonstrates conceptual spaces are superior to mere multidimensional feature spaces in concept learning and confirm the virtue of conceptual spaces.
|Item Type:||Conference Item (Refereed Research Paper - E1)|
|Keywords:||conceptual spaces; knowledge representation|
|Date Deposited:||01 Oct 2009 02:04|
|FoR Codes:||08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified @ 80%
09 ENGINEERING > 0909 Geomatic Engineering > 090903 Geospatial Information Systems @ 20%
|SEO Codes:||89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890202 Application Tools and System Utilities @ 50%
89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890205 Information Processing Services (incl. Data Entry and Capture) @ 40%
89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 10%
|Citation Count from Web of Science||