Presentation 2008-11-27
An Approach to Natural Intelligence Based on Mental Image Directed Semantic Theory
Masao YOKOTA,
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Abstract(in English) Artificial intelligence as imitation of natural intelligence has conventionally been realized with formal representation employed for symbolic logic, etc. or without such representation but with neural network, etc. The author has proposed his original semantic theory "Mental Image Directed Semantic Theory (MIDST)" and has been attempting seamless combination of these two different kinds of methodology by formalizing mental images as root media for human thought within symbolic logic, challenging to model natural intelligence as a deductive system. This paper presents a brief sketch of the attempt on systematic representation and computation of subjective spatiotemporal knowledge in natural language according to a certain hypothesis on mental image formation in human.
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Keyword(in English) Artificial Intelligence / Natural Intelligence / Knowledge Representation / Mental Image / Deductive System
Paper # KBSE2008-29
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Committee KBSE
Conference Date 2008/11/20(1days)
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Registration To Knowledge-Based Software Engineering (KBSE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) An Approach to Natural Intelligence Based on Mental Image Directed Semantic Theory
Sub Title (in English)
Keyword(1) Artificial Intelligence
Keyword(2) Natural Intelligence
Keyword(3) Knowledge Representation
Keyword(4) Mental Image
Keyword(5) Deductive System
1st Author's Name Masao YOKOTA
1st Author's Affiliation Faculty of Information Engineering, Fukuoka Institute of Technology()
Date 2008-11-27
Paper # KBSE2008-29
Volume (vol) vol.108
Number (no) 326
Page pp.pp.-
#Pages 6
Date of Issue