Hexagon-based Q-learning for object search with multiple robots
- Authors
- Yoon, H.-U.; Sim, K.-B.
- Issue Date
- Aug-2005
- Publisher
- SPRINGER-VERLAG BERLIN
- Citation
- ADVANCES IN NATURAL COMPUTATION, PT 3, PROCEEDINGS, v.3612, no.PART III, pp 713 - 722
- Pages
- 10
- Journal Title
- ADVANCES IN NATURAL COMPUTATION, PT 3, PROCEEDINGS
- Volume
- 3612
- Number
- PART III
- Start Page
- 713
- End Page
- 722
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/53206
- DOI
- 10.1007/11539902_88
- ISSN
- 0302-9743
1611-3349
- Abstract
- This paper presents the hexagon-based Q-leaning for object search with multiple robots. We set up an experimental environment with five small mobile robots, obstacles, and a target object. The robots were out to search for a target object while navigating in a hallway where some obstacles were placed. In this 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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