Learning action selection network of intelligent agent

Eun Kyung Yun; Sung Bae Cho

doi:10.1007/978-3-540-24581-0_49

Learning action selection network of intelligent agent

Eun Kyung Yun, Sung Bae Cho

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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 language	English
Title of host publication	AI 2003
Subtitle of host publication	Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings
Editors	Tamas D. Gedeon, Lance Chun Che Fung, Tamas D. Gedeon
Publisher	Springer Verlag
Pages	578-589
Number of pages	12
ISBN (Print)	9783540206460
DOIs	https://doi.org/10.1007/978-3-540-24581-0_49
Publication status	Published - 2003
Event	16th Australian Conference on Artificial Intelligence, AI 2003 - Perth, Australia Duration: 2003 Dec 3 → 2003 Dec 5

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2903
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	16th Australian Conference on Artificial Intelligence, AI 2003
Country/Territory	Australia
City	Perth
Period	03/12/3 → 03/12/5

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2003.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-24581-0_49

Cite this

Yun, E. K., & Cho, S. B. (2003). Learning action selection network of intelligent agent. In T. D. Gedeon, L. C. C. Fung, & T. D. Gedeon (Eds.), AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings (pp. 578-589). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2903). Springer Verlag. https://doi.org/10.1007/978-3-540-24581-0_49

Yun, Eun Kyung ; Cho, Sung Bae. / Learning action selection network of intelligent agent. AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. editor / Tamas D. Gedeon ; Lance Chun Che Fung ; Tamas D. Gedeon. Springer Verlag, 2003. pp. 578-589 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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author = "Yun, {Eun Kyung} and Cho, {Sung Bae}",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2003.; 16th Australian Conference on Artificial Intelligence, AI 2003 ; Conference date: 03-12-2003 Through 05-12-2003",

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Yun, EK & Cho, SB 2003, Learning action selection network of intelligent agent. in TD Gedeon, LCC Fung & TD Gedeon (eds), AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2903, Springer Verlag, pp. 578-589, 16th Australian Conference on Artificial Intelligence, AI 2003, Perth, Australia, 03/12/3. https://doi.org/10.1007/978-3-540-24581-0_49

Learning action selection network of intelligent agent. / Yun, Eun Kyung; Cho, Sung Bae.
AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. ed. / Tamas D. Gedeon; Lance Chun Che Fung; Tamas D. Gedeon. Springer Verlag, 2003. p. 578-589 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2903).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - 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.

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Yun EK, Cho SB. Learning action selection network of intelligent agent. In Gedeon TD, Fung LCC, Gedeon TD, editors, AI 2003: Advances in Artificial Intelligence - 16th Australian Conference on AI, Proceedings. Springer Verlag. 2003. p. 578-589. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-24581-0_49

Learning action selection network of intelligent agent

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