Presentation 2008-06-19
A Robot Control Method Based on Granularity Generated from Rough Sets
Seiki UBUKATA, Yasuo KUDO, Tetsuya MURAI,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) In this paper, we discuss how we can processing information from a point of view of rough-set-based granularity. This study aims to solve conflict resolution problem in Behavior-Based AI based on granularity. As an example, we deal with the robot's garbage collection problem. This robot solves conflict resolution problem by using if-then rules and a network among if-then rules. The solution is equivalent to approximating the concept of action from finite knowledge. Then, we interpret how the lower and the upper approximation can be generated by the network among if-then rules. We also consider use of variable precision rough set model when we cannot obtain the lower approximation.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Rough set / Granularity / Behavior-Based AI
Paper # DE2008-5,PRMU2008-23
Date of Issue

Conference Information
Committee PRMU
Conference Date 2008/6/12(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Robot Control Method Based on Granularity Generated from Rough Sets
Sub Title (in English)
Keyword(1) Rough set
Keyword(2) Granularity
Keyword(3) Behavior-Based AI
1st Author's Name Seiki UBUKATA
1st Author's Affiliation Graduate School of Information Science and Technology()
2nd Author's Name Yasuo KUDO
2nd Author's Affiliation Department of Computer Science and Systems Engineering, Muroran Institute of Technology
3rd Author's Name Tetsuya MURAI
3rd Author's Affiliation Graduate School of Information Science and Technology
Date 2008-06-19
Paper # DE2008-5,PRMU2008-23
Volume (vol) vol.108
Number (no) 94
Page pp.pp.-
#Pages 5
Date of Issue