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- Title
Extended Flocking Algorithm for Self-parameter Tuning.
- Authors
YAMAUCHI, SHO; KAWAMURA, HIDENORI; SUZUKI, KEIJI
- Abstract
SUMMARY Flocking algorithms for a multiagent system are distributed algorithms that only have simple rules for each agent but generate complex formational movement. These algorithms are known as swarm intelligence and are robust and disaster tolerant for most cases. We consider that flocking algorithms that have these characteristics are the way to generate homeostasis in a system. We expect that by making use of this algorithm the system can tune its self-parameters and thus maintain a high performance. First, to apply a flocking algorithm to a system, we extended the flocking algorithm to form an arbitrary lattice for further flexibility. We then applied the extended flocking algorithm to position tracking camera system as an example.
- Subjects
SWARM intelligence; CELLULAR automata; DISTRIBUTED artificial intelligence; ALGORITHMS; ELECTRONICS; ELECTRICAL engineering
- Publication
Electronics & Communications in Japan, 2015, Vol 98, Issue 4, p44
- ISSN
1942-9533
- Publication type
Article
- DOI
10.1002/ecj.11650