Generation of fuzzy rules and learning algorithms for cooperative behavior of Autonomouse Mobile Robots(AMRs)

Jang Hyun Kim, Jin Bae Park, Hyun Seok Yang, Young Pil Park

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

Complex "lifelike" behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, "flocking" and "arrangement" of multiple autonomouse mobile robots are represented by a small number of fuzzy rules. Fuzzy rules in Sugeno type and their related parameters are automatically generated from clustering input-output data obtained from the algorithms for the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.

Original languageEnglish
Pages (from-to)1015-1024
Number of pages10
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume3613
Issue numberPART I
Publication statusPublished - 2005 Oct 27
EventSecond International Confernce on Fuzzy Systems and Knowledge Discovery, FSKD 2005 - Changsha, China
Duration: 2005 Aug 272005 Aug 29

Fingerprint

Cooperative Behavior
Fuzzy rules
Fuzzy Rules
Mobile Robot
Mobile robots
Learning algorithms
Learning Algorithm
Flocking
Artificial Life
Local Interaction
Arrangement
Clustering
Output
Demonstrate
Simulation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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