Hexagon-based Q-learning for object search with multiple robots
- Authors
- Yang, H.-C.; Kim, H.-D.; Sim, K.-B.
- Issue Date
- Jan-2007
- Keywords
- Area-Based action making; Hexagon-based Q-learning; Markovian; Multiple robots
- Citation
- Proceedings of the 12th International Symposium on Artificial Life and Robotis, AROB 12th'07, pp 573 - 576
- Pages
- 4
- Journal Title
- Proceedings of the 12th International Symposium on Artificial Life and Robotis, AROB 12th'07
- Start Page
- 573
- End Page
- 576
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/55215
- ISSN
- 0000-0000
- Abstract
- This paper presents the hexagon-based Q-leaning for object search with multiple robots. We organized an experimental environment with five small mobile robots, obstacles, and an object. Then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used three control algorithms: a random search, an area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning to enhance the area-based action making process.
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Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
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