Autonomous Addition of Agents to an Existing Group Using Genetic Algorithm

Abstract

This paper presents an idea of how new agents can be added autonomously to a group of existing agents without changing the existing communication topology among them. Autonomous agent addition to existing Multi-Agent Systems (MASs) can give a strategic advantage during the execution of a critical beyond visual line-of-sight (BVLOS) mission. The addition of the agent essentially means that new connections with existing agents are established. It is obvious that the consensus control energy increases as the number of agent increases considering a specific consensus protocol. The objective of this work is to establish the new connections in a way such that the consensus energy increase due to the new agents is minimal. The updated topology, including new connections, must contain a spanning tree to maintain the stability of the MASs network. The updated optimal topology is obtained by solving minimum additional consensus control energy using the Two-Dimensional Genetic Algorithm. The results obtained are convincing.

Research on Optimal Scheduling of Multi-Energy Microgrid Based on Stackelberg Game

“…In the evolution process of different populations, the migration operator introduces the optimal individuals to other populations every certain number of iterations, which realizes the information exchange between different populations and the balance of global and local search performance. Secondly, the elite population is established, and each generation of evolution selects the best individuals of other populations to join the elite population and save them through artificial selection operators, and no genetic operation is carried out to ensure that the best individuals are not destroyed, so all the optimal solutions produced by each evolution can be completely preserved [26][27][28][29]. The simplified process of improvement is shown in Figure 3.…”

“…The output constraint and climbing constraint of gas-fired boilers are similar to those of coal-fired units, as shown in Formulas ( 27)- (29).…”

Two-Dimensional Quantum Genetic Algorithm: Application to Task Allocation Problem

“…In [ 28 ], a genetic algorithm with a multidimensional chromosome is used to describe nodes belonging to multiple communities in dense overlapping communities. Another critical and new application of 2D-GA is found in [ 29 , 30 ]. The objective of this paper is to obtain an optimal communication topology to achieve consensus among agents such that the consensus control energy of the agents is minimized.…”