Generation of behavior automaton on neural network

Tetsuya Ogata, Kazuki Hayashi, Ikuo Kitagishi, Shigeki Sugano

Research output: Contribution to conferencePaper

Abstract

To plan behavior procedures, it is necessary for an agent to have a world model concerning the temporal sequences information. In this paper, a temporal information learning algorithm is proposed with a three layer neural network implemented the `effectiveness of simulation accumulation' algorithm. This algorithm can construct `behavior automaton' in the neural network. From the results of some learning experiments using a mobile robot simulation, the generated automaton express the complexity of the simulation environments. The robot agent acquires a behavior automaton for obstacle avoidance behavior which is influenced by the simulation environment.

Original languageEnglish
Pages608-613
Number of pages6
Publication statusPublished - 1997 Dec 1
EventProceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Part 2 (of 3) - Grenoble, Fr
Duration: 1998 Sep 71998 Sep 11

Other

OtherProceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Part 2 (of 3)
CityGrenoble, Fr
Period98/9/798/9/11

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

Cite this

Ogata, T., Hayashi, K., Kitagishi, I., & Sugano, S. (1997). Generation of behavior automaton on neural network. 608-613. Paper presented at Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Part 2 (of 3), Grenoble, Fr, .