  Formation control problem is one of the most concerned topics within the
realm of swarm intelligence, which is usually solved by conventional
mathematical approaches. In this paper, however, we presents a metaheuristic
approach that leverages a natural co-evolutionary strategy to solve the
formation control problem for a swarm of missiles. The missile swarm is modeled
by a second-order system with heterogeneous reference target, and exponential
error function is made to be the objective function such that the swarm
converge to optimal equilibrium states satisfying certain formation
requirements. Focusing on the issue of local optimum and unstable evolution, we
incorporate a novel model-based policy constraint and a population adaptation
strategies that greatly alleviates the performance degradation. With
application of the Molloy-Reed criterion in the field of network communication,
we developed an adaptive topology method that assure the connectivity under
node failure and its effectiveness are validated both theoretically and
experimentally. Experimental results valid the effectiveness of the proposed
formation control approach. More significantly, we showed that it is feasible
to treat generic formation control problem as Markov Decision Process(MDP) and
solve it through iterative learning.

Systems and Control;Multiagent Systems;Neural and Evolutionary Computing;Systems and Control