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Active leading through obstacles using ant-colony algorithm

Vatankhah, R ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.neucom.2011.08.030
  3. Abstract:
  4. In presence of obstacles, inter-agent pulling actions must be bounded. In this case, to remain connected to the group, the leader-agent (LA) must perform an active leading strategy. In this paper, an active leading algorithm is proposed which monitors the neighborhood of the LA and adjusts its velocity. The algorithm is based on the ant colony optimization (ACO) technique. As a real time optimization package, the ACO algorithm maximizes influence of the LA on the group, leading to fast flocking. Comparison with another optimization method is provided as well. Simulations show that the algorithm is successful and cost effective
  5. Keywords:
  6. Ant colony algorithm ; Multi-agents ; ACO algorithms ; Active leader ; Ant colony algorithms ; Ant Colony Optimization (ACO) ; Ant-colony algorithm ; Cost effective ; Multi agent ; Optimization method ; Real-time optimization ; Algorithms ; Active leading ; Algorithm ; Ant colony optimization algorithm ; Artificial intelligence ; Computer simulation ; Fast flocking ; Genetic algorithm ; Information system ; kinematics ; Machine learning ; Mathematical computing ; Priority journal ; Process optimization ; Robotics ; Velocity
  7. Source: Neurocomputing ; Volume 88 , 2012 , Pages 67-77 ; 09252312 (ISSN)
  8. URL: http://www.sciencedirect.com/science/article/pii/S0925231212000136