Learning action selection network of intelligent agent

Eun Kyung Yun, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


Behavior-based artificial intelligent system is to derive the complicated behaviors by selecting appropriate one from a set of basic behaviors. Many robot systems have used behavior-based systems since the 1980’s. In this paper, we propose new method to create the sequences of behaviors appropriate to the changing environments by adding the function of learning with Learning Classifier System to P. Maes’ action selection network. Links of the network need to be reorganize as the problem changes, because each link is designed initially according to the given problem and is fixed. Learning Classifier System is suitable for learning of rule-based system in changing environments. The simulation results with Khepera robot simulator show the usefulness of learning in the action selection network by generating appropriate behaviors.

Original languageEnglish
Title of host publicationAI 2003
Subtitle of host publicationAdvances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings
EditorsTamas D. Gedeon, Lance Chun Che Fung, Tamas D. Gedeon
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783540206460
Publication statusPublished - 2003
Event16th Australian Conference on Artificial Intelligence, AI 2003 - Perth, Australia
Duration: 2003 Dec 32003 Dec 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other16th Australian Conference on Artificial Intelligence, AI 2003

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2003.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


Dive into the research topics of 'Learning action selection network of intelligent agent'. Together they form a unique fingerprint.

Cite this