Volume 5, Issue 1, June 2018, Pages 67 - 70
Efficient collective search by agents that remember failures
Authors
Masao Kubomasaok@nda.ac.jp
Department of Computer Science, National Defense Academy, Hashirimizu 1-10-20, Yokosuka, Kanagawa, 239-8686, Japan
Nhuhai Phunged17006@nda.ac.jp
Department of Computer Science, National Defense Academy, Hashirimizu 1-10-20, Yokosuka, Kanagawa, 239-8686, Japan
Hiroshi Satohsato@nda.ac.jp
Department of Computer Science, National Defense Academy, Hashirimizu 1-10-20, Yokosuka, Kanagawa, 239-8686, Japan
Available Online 30 June 2018.
- DOI
- 10.2991/jrnal.2018.5.1.15How to use a DOI?
- Keywords
- Swarm intelligence; Machine learning; Complex systems; Best-of-n problem
- Abstract
The BRT agent is an algorithm that can find appropriate collective behavior by changing the agreement contents in a trial and error manner. Computer experiments show that it is necessary to change the agreement contents the number of times that is proportional to the square of the number of choices. In this paper, we attempted to shorten this search time by introducing an agent that memorizes actions that were not able to achieve the expected effect of what they executed. As a result, we found that search time can be improved by just mixing a few this proposed taboo list agents.
- Copyright
- Copyright © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
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Cite this article
TY - JOUR AU - Masao Kubo AU - Nhuhai Phung AU - Hiroshi Sato PY - 2018 DA - 2018/06/30 TI - Efficient collective search by agents that remember failures JO - Journal of Robotics, Networking and Artificial Life SP - 67 EP - 70 VL - 5 IS - 1 SN - 2352-6386 UR - https://doi.org/10.2991/jrnal.2018.5.1.15 DO - 10.2991/jrnal.2018.5.1.15 ID - Kubo2018 ER -