Abstract
Swarm robots are highly desirable in dealing with complex tasks. However, manual coding of individual robot behaviours and robot collaboration is not trivial especially under unknown and dynamic environments. This study introduced a hyper-heuristic methodology for this challenge, so robots can learn suitable behaviours during the process. The hyper-heuristic method creates actions based on a set of low-level heuristics and improves these actions through autonomous heuristic adjustment. A collective negotiation and updating mechanism is proposed so the robot swarm performance can be improved. We evaluate this method on the problem of building surface cleaning. Experiments show the effectiveness of the hyper-heuristic method and the collective learning mechanism.
Original language | English |
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Title of host publication | PRICAI 2018: Trends in Artificial Intelligence |
Subtitle of host publication | 15th Pacific Rim International Conference on Artificial Intelligence Nanjing, China, August 28–31, 2018 Proceedings, Part II |
Editors | Xin Geng, Byeong-Ho Kang |
Place of Publication | Cham Switzerland |
Publisher | Springer |
Pages | 499-507 |
Number of pages | 9 |
ISBN (Electronic) | 9783319973104 |
ISBN (Print) | 9783319973098 |
DOIs | |
Publication status | Published - 2018 |
Event | Pacific Rim International Conference on Artificial Intelligence 2018 - Nanjing, China Duration: 28 Aug 2018 → 31 Aug 2018 Conference number: 15th http://cse.seu.edu.cn/pricai18/ |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer |
Volume | 11013 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | Pacific Rim International Conference on Artificial Intelligence 2018 |
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Abbreviated title | PRICAI 2018 |
Country | China |
City | Nanjing |
Period | 28/08/18 → 31/08/18 |
Internet address |
Keywords
- Collective behaviours
- Hyper heuristics
- Swarm robots