Title :
Analysis of BEECLUST swarm algorithm
Author_Institution :
Dept. of Eng. & Phys., Murray State Univ., Murray, KY, USA
Abstract :
We analyze a new swarm search algorithm based on the behavior of social insects, specifically honey bees. The new algorithm does not require any agent-agent communication and does not require the agents to know position information. The agents, or bots, cluster together near peaks in the search space based on the fitness value at the locations where the agents collide. In this paper we describe the algorithm, model the algorithm using a birth and death Markov chain, and determine the expected time for the agents/bots to cluster. We also determine the swarm size needed to complete a search in a reasonable time frame.
Keywords :
Markov processes; multi-agent systems; particle swarm optimisation; search problems; BEECLUST swarm algorithm; agent-agent communication; birth-death Markov chain; honey bees behavior; social insects behavior; swarm search algorithm; Algorithm design and analysis; Clustering algorithms; Equations; Markov processes; Mathematical model; Steady-state; Time measurement; BEECLUST; Markov chain; swarm algorithms; swarm robotics;
Conference_Titel :
Swarm Intelligence (SIS), 2011 IEEE Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-61284-053-6
DOI :
10.1109/SIS.2011.5952587
