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 language | English |
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| Pages | 608-613 |
| Number of pages | 6 |
| Publication status | Published - 1997 Dec 1 |
| Event | Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Part 2 (of 3) - Grenoble, Fr Duration: 1998 Sept 7 → 1998 Sept 11 |
Other
| Other | Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Part 2 (of 3) |
|---|---|
| City | Grenoble, Fr |
| Period | 98/9/7 → 98/9/11 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications