This paper studies a non-reciprocal swarm model that consists of a group of mobile autonomous agents with an attraction-repulsion function governing the interaction of the agents. The function is chosen to have infinitely large values of repulsion for vanishing distance between two agents so as to avoid occurrence of collision. It is shown analytically that under the detailed balance condition in coupling weights, all the agents will aggregate and eventually form a cohesive cluster of finite size around the weighted center of the swarm in a finite time. Moreover, the swarm system is completely stable, namely, the motion of all agents converge to the set of equilibrium points. For the general case of non-reciprocal swarms without the detailed balance condition, numerical simulations show that more complex self-organized oscillations can emerge in the swarms. The effect of noise on collective dynamics of the swarm is also examined with a white Gaussian noise model.
This paper considers a type of multi-agent systems.The interactions among the individual agents are assumed to...
Chen Zhifu,Chu Tianguang Intelligent Control Laboratory,Center for Systems and Control,College of Engineering,Peking University,Beijing 100871,P.R.China
This paper studies the evolutionary prisoner's dilemma game on a highly clustered community network in which the clustering coefficient and the community size can be tuned. It finds that the clustering coefficient in such a degree- homogeneous network inhibits the emergence of cooperation for the entire range of the payoff parameter. Moreover, it finds that the community size can also have a marked influence on the evolution of cooperation, with a larger community size leading to not only a lower cooperation level but also a smaller threshold of the payoff parameter above which cooperators become extinct.
This paper studies the consensus problems for a group of agents with switching topology and time-varying communication delays,where the dynamics of agents is modeled as a high-order integrator.A linear distributed consensus protocol is proposed,which only depends on the agent's own information and its neighbors'partial information.By introducing a decomposition of the state vector and performing a state space transformation,the closed-loop dynamics of the multi-agent system is converted into two decoupled subsystems.Based on the decoupled subsystems,some sufficient conditions for the convergence to consensus are established,which provide the upper bounds on the admissible communication delays.Also,the explicit expression of the consensus state is derived.Moreover,the results on the consensus seeking of the group of high-order agents have been extended to a network of agents with dynamics modeled as a completely controllable linear time-invariant system.It is proved that the convergence to consensus of this network is equivalent to that of the group of high-order agents.Finally,some numerical examples are given to demonstrate the effectiveness of the main results.
Fangcui JIANG,Long WANG,Guangming XIE(Institute of Intelligent Engineering,Center for Systems and Control,College of Engineering,and Key Laboratory of Machine Perception(Ministry of Education),Peking University,Beijing 100871,China)
This paper investigates the controllability of multi-agent systems based on agreement protocols. First, for a group of single-integrator agents, the controllability is studied in a unified framework for both networks with leader-following structure and networks with undirected graph. Some new necessary/sufficient conditions for the controllability of networks of single-integrator agents are established. Second, we prove that, under the same topology and same prescribed leaders, a network of high-order dynamic agents is completely controllable if and only if so is a network of single-integrator agents. Third, how the selection of leaders and the coupling weights of graphs affect the controllability is analyzed. Finally, some numerical simulations are presented to demonstrate the effectiveness of the theoretical results.
We study the effect of accumulative payoff on the evolution of cooperation in the evolutionary prisoner's dilemma on a square lattice. We introduce a decaying factor for the accumulative payoff, which characterizes the extent that the historical payoff is accumulated. It is shown that for fixed values of the temptation to defect, the density of cooperators increases with the value of the decaying factor. This indicates that the more the historical payoff is involved, the more favourable cooperators become. In the critical region where the cooperator density converges to zero, cooperators vanish according to a power-law-like behaviour. The associated exponents agree approximately with the two-dimensional directed percolation and depend weakly on the value of the decaying factor.
