The Effect of Sensory Blind Zones on Milling Behavior in a Dynamic Self-Propelled Particle Model

Emergent pattern formation in self-propelled particle (SPP) systems is extensively studied because it addresses a range of swarming phenomena which occur without leadership. Here we present a dynamic SPP model in which a sensory blind zone is introduced into each particle's zone of interaction. Using numerical simulations we discovered that the degradation of milling patterns with increasing blind zone ranges undergoes two distinct transitions, including a new, spatially nonhomogeneous transition that involves cessation of particles' motion caused by broken symmetries in their interaction fields. Our results also show the necessity of nearly complete panoramic sensory ability for milling behavior to emerge in dynamic SPP models, suggesting a possible relationship between collective behavior and sensory systems of biological organisms.Comment: 12 pages, 4 figure

Formation of regular spatial patterns in ratio-dependent predator-prey model driven by spatial colored-noise

Results are reported concerning the formation of spatial patterns in the two-species ratio-dependent predator-prey model driven by spatial colored-noise. The results show that there is a critical value with respect to the intensity of spatial noise for this system when the parameters are in the Turing space, above which the regular spatial patterns appear in two dimensions, but under which there are not regular spatial patterns produced. In particular, we investigate in two-dimensional space the formation of regular spatial patterns with the spatial noise added in the side and the center of the simulation domain, respectively.Comment: 4 pages and 3 figure

Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations

Collective, especially group-based, managerial decision making is crucial in organizations. Using an evolutionary theoretic approach to collective decision making, agent-based simulations were conducted to investigate how human collective decision making would be affected by the agents' diversity in problem understanding and/or behavior in discussion, as well as by their social network structure. Simulation results indicated that groups with consistent problem understanding tended to produce higher utility values of ideas and displayed better decision convergence, but only if there was no group-level bias in collective problem understanding. Simulation results also indicated the importance of balance between selection-oriented (i.e., exploitative) and variation-oriented (i.e., explorative) behaviors in discussion to achieve quality final decisions. Expanding the group size and introducing non-trivial social network structure generally improved the quality of ideas at the cost of decision convergence. Simulations with different social network topologies revealed collective decision making on small-world networks with high local clustering tended to achieve highest decision quality more often than on random or scale-free networks. Implications of this evolutionary theory and simulation approach for future managerial research on collective, group, and multi-level decision making are discussed.Comment: 27 pages, 5 figures, 2 tables; accepted for publication in Complexit

Karakteristik Petani Padi Peserta Program Upaya Khusus Padi Jagung Kedelai (Upsus Pajale)di Desa Bunga Raya Kecamatan Bunga Raya Kabupaten Siak

This research is intended to understand the characteristic of the farmers, stage on the Specially Efforts Corn, Soybean, Paddy(UPSUS PAJALE) at Bunga Raya village. This research was conducted at Bunga Raya village that is located in the Siak Regency. Multi stage sampling was used as the method to choose locations. The samples were gathered using Purposive Sampling method. This research uses 48 farmers data as samples. Data analysis which is used for this research is the descriptive method. The goals were analyzed using Likert Scale. The results of this research shows us the paddy farmers' internal characteristics at Bunga Raya village such as: the farmers' productive ages are within the range of 40-46 years, most of the farmers' are High School graduates, each farmers' family consists of 4-5 persons, farmers' experiences are between 17-23 years, the land area that the farmers manage is between 0,5-1ha and the farmers are highly cosmopolitans. The external characteristics of farmers are medium when are evaluated according to the instructors' intensity, the accuracy of instructors channel, the amount of information sources, the affordability of production facilities price and the availability of production facilities

Complexity, Development, and Evolution in Morphogenetic Collective Systems

Many living and non-living complex systems can be modeled and understood as collective systems made of heterogeneous components that self-organize and generate nontrivial morphological structures and behaviors. This chapter presents a brief overview of our recent effort that investigated various aspects of such morphogenetic collective systems. We first propose a theoretical classification scheme that distinguishes four complexity levels of morphogenetic collective systems based on the nature of their components and interactions. We conducted a series of computational experiments using a self-propelled particle swarm model to investigate the effects of (1) heterogeneity of components, (2) differentiation/re-differentiation of components, and (3) local information sharing among components, on the self-organization of a collective system. Results showed that (a) heterogeneity of components had a strong impact on the system's structure and behavior, (b) dynamic differentiation/re-differentiation of components and local information sharing helped the system maintain spatially adjacent, coherent organization, (c) dynamic differentiation/re-differentiation contributed to the development of more diverse structures and behaviors, and (d) stochastic re-differentiation of components naturally realized a self-repair capability of self-organizing morphologies. We also explored evolutionary methods to design novel self-organizing patterns, using interactive evolutionary computation and spontaneous evolution within an artificial ecosystem. These self-organizing patterns were found to be remarkably robust against dimensional changes from 2D to 3D, although evolution worked efficiently only in 2D settings.Comment: 13 pages, 8 figures, 1 table; submitted to "Evolution, Development, and Complexity: Multiscale Models in Complex Adaptive Systems" (Springer Proceedings in Complexity Series

Social network dynamics of face-to-face interactions

The recent availability of data describing social networks is changing our understanding of the "microscopic structure" of a social tie. A social tie indeed is an aggregated outcome of many social interactions such as face-to-face conversations or phone-calls. Analysis of data on face-to-face interactions shows that such events, as many other human activities, are bursty, with very heterogeneous durations. In this paper we present a model for social interactions at short time scales, aimed at describing contexts such as conference venues in which individuals interact in small groups. We present a detailed anayltical and numerical study of the model's dynamical properties, and show that it reproduces important features of empirical data. The model allows for many generalizations toward an increasingly realistic description of social interactions. In particular in this paper we investigate the case where the agents have intrinsic heterogeneities in their social behavior, or where dynamic variations of the local number of individuals are included. Finally we propose this model as a very flexible framework to investigate how dynamical processes unfold in social networks.Comment: 20 pages, 25 figure

Effects of Network Connectivity and Diversity Distribution on Human Collective Ideation

Human collectives, e.g., teams and organizations, increasingly require participation of members with diverse backgrounds working in networked social environments. However, little is known about how network structure and the diversity of member backgrounds would affect collective processes. Here we conducted three sets of human-subject experiments which involved 617 participants who collaborated anonymously in a collective ideation task on a custom-made online social network platform. We found that spatially clustered collectives with clustered background distribution tended to explore more diverse ideas than in other conditions, whereas collectives with random background distribution consistently generated ideas with the highest utility. We also found that higher network connectivity may improve individuals' overall experience but may not improve the collective performance regarding idea generation, idea diversity, and final idea quality.Comment: 43 pages, 19 figures, 4 table