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• A proportional-integral (PI) control strategy is introduced to the Vicsek model. • The control parameters can be adjusted to optimize the system synchronization. • The control strategy improves the robustness of the system in the noise environment. • The effect of heterogeneous control parameters on system synchronization is investigated. This paper introduces an adaptive control strategy to the Vicsek model and investigates the collective behavior of self-propelled agents from the perspective of control theory. In the model, each agent adopts the classic proportional-integral (PI) control strategy to adjust its direction based on the deviation from the average direction of local neighbors. It is found that the integral term of the controller can eliminate the steady-state error, but strong integral effect will cause fluctuation of the system and prolong the convergence time. Therefore, the moderate integral control can adjust the headings of all agents to be synchronized after a short transient time. However, the proportional term incurs over-regulation of the directions, thus impeding the global convergence to be achieved. The robustness of the synchronizability with respect to different noise intensities is also investigated. Even in the strong noise environments, the control model can still maintain a high degree of directional consistency by adopting the conservative adjustment strategy. Furthermore, the diversity of control parameter is analyzed by considering the integral parameter following the normal distribution. It reveals that inconsistent adjustment magnitude is unfavorable to the synchronization of the system. [ABSTRACT FROM AUTHOR]

We investigate opinion dynamics of the model in which each agent can communicate with local neighbors whose opinions are inside the bound of confidence and meanwhile selecting long-range neighbors according to a common-neighbors rule. The common-neighbors rule means that two agents sharing more neighbors have larger probability to be connected. We find that increasing communication between agents who have common friends will prolong the time needed for the system to reach a consensus state. In contrast, the long-range connections between agents sharing no friends will promote the convergence of the system. The generality of this observation is tested against different system sizes. Simulation results also show that a large number of long-range connections help the system to reach a consensus fast. [ABSTRACT FROM AUTHOR]

We investigate the evolution of cooperative behaviors of the spatial public goods game on lattices where the number of interactive neighbors are not identical for all players in the population but they can randomly select the interactive objects from the immediate neighbors in the von Neumann or Moore neighborhood. Extensive numerical simulations indicate that the cooperation level is greatly enhanced by the interaction diversity compared with the traditional model in which the social scope is homogeneous. The mechanism that explains this improvement is based on the inhomogeneous interactive domain in which cooperators can maintain their strategies easily and stabilize the cooperative neighborhood, resulting in the emergence of close cooperation clusters. Moreover, increasing uncertainty in strategy adoption process can resolve the trapped condition with a strong synergy factor and help the system to achieve the full cooperation state when the diversity mechanism is considered. [ABSTRACT FROM AUTHOR]

Abstract: In this work we investigate the dynamics of networked evolutionary minority game (NEMG) wherein each agent is allowed to evolve its strategy according to the information obtained from its neighbors in the network. We investigate four kinds of networks, including star network, regular network, random network and scale-free network. Simulation results indicate that the dynamics of the system depends crucially on the structure of the underlying network. The strategy distribution in a star network is sensitive to the precise value of the mutation magnitude L, in contrast to the strategy distribution in regular, random and scale-free networks, which is easily affected by the value of the prize-to-fine ratio R. Under a simple evolutionary scheme, the networked system with suitable parameters evolves to a high level of global coordination among its agents. In particular, the performance of the system is correlated to the clustering property of the network, where larger clustering coefficient leads to better performance. [Copyright &y& Elsevier]

Abstract: In this work, we consider a network of agents who compete for limited resources through a modified evolutionary minority game model based on Kauffman network. The properties of such a system for different values of mean connectivity K of the network are studied. Simulation results suggest that the agents also tend to self-segregate into opposing groups characterized by extreme actions, and show that the agents can coordinate their behavior effectively in the system with . Enhanced cooperation occurs also for a generalization of the model to multiple-choice evolutionary minority games in which the agents are allowed to choose among several options. [Copyright &y& Elsevier]

Most previous works study the evolution of opinions by commonly employing an isolated single network. However, this is not fully consistent with recent identification that interaction between networks plays a crucial rule in the dynamical behaviors taking place on them. In this work, we consider a system including two chains with the same size, entangled with each other by the introduction of probabilistic interconnections and communication. We introduce the Sznajd model into such system and study how the coupling effect influences the evolution of opinions of the whole system. Simulation results show that strong interaction and communication between two interdependent chains promote the whole system to achieve consensus easily. Interestingly, we find that with the increase of connection probability, the time evolutions of magnetization of the two chains are gradually consistent and there exists an intermediate region of intercommunication probability leading to the shortest exit time. In addition, the exit time depends on the numbers of Ising spins in a power-law form. The consensus of one chain can change the critical behavior of the other even with a small connection or communication probability. [ABSTRACT FROM AUTHOR]

Opinion dynamics as a special type of complex human behavior has received increasing attention in recent years. From a control-theoretic point of view, the opinion dynamical system can be viewed as a decentralized control system. In this paper, we investigate opinion dynamics of the model in which each agent can adjust its opinion by using an incremental proportional–integral (PI) controller, where the opinion is updated according to the deviation between the average opinion of local neighbors' and the individual one. Simulation results suggest the strong integral effect can promote the system to achieve consensus easily and reduce the number of subsets fast. In contrast, the proportional effect will impede the convergence of the system and prolong the time required to reach consensus. This observation is robust with different system sizes and provides a new way of thinking about guidance in opinion dynamics. • We propose a decentralized opinion evolution model with proportional–integral (PI) control strategy. • The integral effect of PI controller promotes the system to achieve consensus fast. • The proportional effect of PI controller prolongs the time required to reach consensus. • Control theory provides a new way of thinking about guidance in opinion dynamics. [ABSTRACT FROM AUTHOR]

Slope One algorithm and its descendants measure user-score distance and use the statistical score distance between users to predict unknown ratings, as opposed to the typical collaborative filtering algorithm that uses similarity for neighbor selection and prediction. Compared to collaborative filtering systems that select only similar neighbors, algorithms based on user-score distance typically include all possible related users in the process, which needs more computation time and requires more memory. To improve the scalability and accuracy of distance-based recommendation algorithm, we provide a user-item link prediction approach that combines user distance measurement with similarity-based user selection. The algorithm predicts unknown ratings based on the filtered users by calculating user similarity and removing related users with similarity below a threshold, which reduces 26 to 29 percent of neighbors and improves prediction error, ranking, and prediction accuracy overall. [ABSTRACT FROM AUTHOR]

The link prediction aims at predicting missing or future links in networks, which provides theoretical significance and extensive applications in the related field. However, the degree of confidence in the prediction results has not been fully discussed in related works. In this article, we propose a similarity confidence coefficient and a confidence measure for link prediction. The former is used to balance the reliability of similarity calculation results, which might be untrustworthy due to the information asymmetry in the calculation, and also makes it easier to achieve the optimal accuracy with a smaller number of neighbors. The latter is used to quantify our confidence in the prediction results of each prediction. The experimental results based on the Movie-Lens data set show that prediction accuracy is improved when the similarity between the nodes is corrected by the similarity confidence coefficient. Second, the experiments also confirm that the confidence degree of the link prediction results can be measured quantitatively. Our research indicates that the confidence level on each prediction is determined by the amount of data used in the corresponding calculation, which can be measured quantitatively. [ABSTRACT FROM AUTHOR]

Leymus mollis (2n = 4x = 28, NsNsXmXm), a wild relative of common wheat (Triticum aestivum L.), carries numerous loci which could potentially be used in wheat improvement. In this study, line 17DM48 was isolated from the progeny of a wheat and L. mollis hybrid. This line has 42 chromosomes forming 21 bivalents at meiotic metaphase I. Genomic in situ hybridization (GISH) demonstrated the presence of a pair chromosomes from the Ns genome of L. mollis. This pair substituted for wheat chromosome 2D, as shown by fluorescence in situ hybridization (FISH), DNA marker analysis, and hybridization to wheat 55K SNP array. Therefore, 17DM48 is a wheat-L. mollis 2Ns (2D) disomic substitution line. It shows longer spike and a high level of stripe rust resistance. Using specific-locus amplified fragment sequencing (SLAF-seq), 13 DNA markers were developed to identify and trace chromosome 2Ns of L. mollis in wheat background. This line provides a potential bridge germplasm for genetic improvement of wheat stripe rust resistance. [ABSTRACT FROM AUTHOR]