Survey of Flocking Algorithms in Multi-agent Systems

Flocking behaviour in Multi-agent Systems (MAS) has attracted tremendous attention amongst researchers in the recent past due to its potential applications in various fields where distributed work environment is desired. The flocking algorithms have the potential to introduce self-organizing, self-healing and selfconfiguring capabilities in the functioning of a distributed system. The flocking algorithms exploit various artificial intelligence techniques, mathematical potential functions and geometric approaches to realize the global objectives by controlling local parameters. The main parameters of characterization of any flocking algorithm consist of mathematical models of agents, their hierarchical or flat control structures and the control approach by which these agents are controlled to exhibit flocking behaviour along with any type of formational constraints. A rigorous survey study of flocking algorithms for agents in MAS in the perspective of various instances of agents shows that there lies a huge scope for the researchers to apply, experiment and analyse various techniques locally to achieve global objectives. This paper surveys the flocking algorithms in perspective of these parameters.