Presentation 1994/3/4
Experience-Based Reasoning and Learning
Shigenobu Kobayashi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In the AI world,for 20 years,rule-based reasoning and knowledge acquisition and refinement by machine learning have been the dominant paradigms.On the other hand,the difficulty of extracting generalized rules and the brittleness of rule-based reasoning have been often pointed out. In the last five years,memory-based reasoning,case-based reasoning and reinforcement learning have become the object of attention as experience-based reasoning and learning technology. The purpose of this article is to describe the background of paradigms shift in reasoning and learning,to discuss features of new technology and to consider the future development.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Experience-Based Reasoning / Experience-Based Learning / Memory- Based Reasoning / Case-Based Reasoning / Analogical Reasoning / Reinforcement Learning
Paper # AI93-83,KBSE93-50
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Conference Information
Committee AI
Conference Date 1994/3/4(1days)
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Paper Information
Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Experience-Based Reasoning and Learning
Sub Title (in English)
Keyword(1) Experience-Based Reasoning
Keyword(2) Experience-Based Learning
Keyword(3) Memory- Based Reasoning
Keyword(4) Case-Based Reasoning
Keyword(5) Analogical Reasoning
Keyword(6) Reinforcement Learning
1st Author's Name Shigenobu Kobayashi
1st Author's Affiliation Department of Intelligence Science Interdisciplinary,Graduate School of Science and Engineering,Tokyo Institute of Technology()
Date 1994/3/4
Paper # AI93-83,KBSE93-50
Volume (vol) vol.93
Number (no) 493
Page pp.pp.-
#Pages 8
Date of Issue