The development and interaction of terrorist and fanatic groups

Through the mathematical study of two models we quantify some of the theories of co-development and co-existence of focused groups in the social sciences. This work attempts to develop the mathematical framework behind the social sciences of community formation. By using well developed theories and concepts from ecology and epidemiology we hope to extend the theoretical framework of organizing and self-organizing social groups and communities, including terrorist groups. The main goal of our work is to gain insight into the role of recruitment and retention in the formation and survival of social organizations. Understanding the underlining mechanisms of the spread of ideologies under competition is a fundamental component of this work. Here contacts between core and non-core individuals extend beyond its physical meaning to include indirect interaction and spread of ideas through phone conversations, emails, media sources and other similar mean. This work focuses on the dynamics of formation of interest groups, either ideological, economical or ecological and thus we explore the questions such as, how do interest groups initiate and co-develop by interacting within a common environment and how do they sustain themselves? Our results show that building and maintaining the core group is essential for the existence and survival of an extreme ideology. Our research also indicates that in the absence of competitive ability (i.e., ability to take from the other core group or share prospective members) the social organization or group that is more committed to its group ideology and manages to strike the right balance between investment in recruitment and retention will prevail. Thus under no cross interaction between two social groups a single trade-off (of these efforts) can support only a single organization. The more efforts that an organization implements to recruit and retain its members the more effective it will be in transmitting the ideology to other vulnerable individuals and thus converting them to believers.     

The Emergence of Racial Segregation in an Agent-Based Model of Residential Location: The Role of Competing Preferences

Models of segregation dynamics have examined how individual preferences over neighborhood racial composition determine macroscopic patterns of segregation. Many fewer models have considered the role of household preferences over other location attributes, which may compete with preferences over racial composition. We hypothesize that household preferences over location characteristics other than racial composition affect segregation dynamics in nonlinear ways and that, for a critical range of parameter values, these competing preferences can qualitatively affect segregation outcomes. To test this hypothesis, we develop a dynamic agent-based model that examines macro-level patterns of segregation as the result of interdependent household location choices. The model incorporates household preferences over multiple neighborhood features, some of which are endogenous to residential location patterns, and allows for income heterogeneity across races and among households of the same race. Preliminary findings indicate that patterns of segregation can emerge even when individuals are wholly indifferent to neighborhood racial composition, due to competing preferences over neighborhood density. Further, the model shows a strong tendency to concentrate affluent families in a small number of suburbs, potentially mimicking recent empirical findings on favored quarters in metropolitan areas. This paper was the first runner-up for the 2004 NAACSOS best paper award. Kan Chen is an associate professor in the Department of Computational Science at the National University of Singapore. His recent research interests include spatial and temporal scaling in driven, dissipative systems, applications of self-organized criticality, dynamics of earthquakes, and computational finance. He received a B.Sc. in physics from the University of Science and Technology of China (1983) and a Ph.D. in physics from Ohio State University (1988). Elena Irwin is an associate professor in the Department of Agricultural, Environmental, and Development Economics at Ohio State University. Her research interests include land use change, urban sprawl, household location decisions, and the value of open space. This research applies theory and modeling techniques from the fields of spatial and regional economics, including the application of spatial econometrics and geographic information systems (GIS). She received a B.A. in German and History from Washington University in St. Louis (1988) and a Ph.D. in Agricultural and Resource Economics from the University of Maryland (1998). Ciriyam Jayaprakash is a Professor in the Department of Physics at the Ohio State University. His recent research interests include spatially extended nonlinear systems including fully-developed turbulence, genetic regulatory networks, and applications of statistical mechanical techniques to financial and social sciences. He received an M.S. in Physics from the Indian Institute of Technology, Kanpur (1973), an M.S. in Physics from Caltech (1975) and a Ph.D in Physics from the University of Illinois at Urbana-Champaign (1979). Keith Warren is an assistant professor in the College of Social Work at Ohio State University. His research interests focus on interpersonal interactions in the development and solution of social problems, particularly those of urban areas such as segregation, substance abuse and increased interpersonal violence. He received a B.A in Behavioral Science from Warren Wilson College (1984), and a Ph.D. in Social Work from the University of Texas at Austin (1998)     

Reduced Dynamics of the Non-holonomic Whipple Bicycle

Though the bicycle is a familiar object of everyday life, modeling its full nonlinear three-dimensional dynamics in a closed symbolic form is a difficult issue for classical mechanics. In this article, we address this issue without resorting to the usual simplifications on the bicycle kinematics nor its dynamics. To derive this model, we use a general reduction-based approach in the principal fiber bundle of configurations of the three-dimensional bicycle. This includes a geometrically exact model of the contacts between the wheels and the ground, the explicit calculation of the kernel of constraints, along with the dynamics of the system free of any external forces, and its projection onto the kernel of admissible velocities. The approach takes benefits of the intrinsic formulation of geometric mechanics. Along the path toward the final equations, we show that the exact model of the bicycle dynamics requires to cope with a set of non-symmetric constraints with respect to the structural group of its configuration fiber bundle. The final reduced dynamics are simulated on several examples representative of the bicycle. As expected the constraints imposed by the ground contacts, as well as the energy conservation, are satisfied, while the dynamics can be numerically integrated in real time.     

Global stability in a structured population competition model with distributed maturation delay and harvesting

This paper is concerned with a delay differential equation model for the interaction between two species, the adult members of which are in competition, with stage-structure and harvesting of the mature and immature members of each species. The maturation delay for each species is modelled as a distribution, to allow for the possibility that individuals may take a different amount of time to mature. General birth and death rate functions are used. We find that the dynamics of the model depends largely on the birth and death functions, which depend on the total number of adults.We study the dynamics of our model analytically and we present results on the positivity and boundedness of the solutions, and global stability results are established for each equilibrium.     

Identity-based learning and segregation in social networks under different institutional environments

To study the evolution of segregation in social networks across systems embedded in different institutional environments, we develop an identity-based learning model where segregation is stochastically conditioned by the initial distribution of the actor’s attention to identity and the updating of this distribution over time. The updating process, which we call the process of mutual learning multiplier, is based on an actor’s success and failure experiences in tying with the same-subgroup and cross-subgroup actors. Results from a Monte Carlo simulation of the model show that the mutual learning multiplier produces disproportional relationships between the initial distribution of identity attention and the level of segregation in social networks. We also find that those relationships are affected by the actors’ attention to structural holes, rate of learning from experience, system size, and the identity heterogeneity of the system. Overall, the model provides insights into various dynamics of network structuration across time and space.     

Decentralized and dynamic group formation of reconfigurable agents

Adaptive group formation in dynamic environments performed by heterogeneous swarms of simple agents is an interesting research topic. In this paper we consider an unsupervised scenario where the individuals of the swarm have limited information about their environment as well as limited communication capabilities. The particular case of a multi-agent model with self-organized reconfigurable agents where the agents are confronted with a resource collection task, different movement, and group formation tactics are analyzed experimentally. It is shown that cooperation in groups is profitable for the group members and the optimal group size depends on environmental parameters. Moreover, a simple strategy based on the agents ability to measure their own workload results in an adaptive behavior that influences the size of the groups and increases the performance of the overall system.     

Lotka-Volterra's model and migrations: Breaking of the well-known center

This paper is devoted to the study of the effect of individual behavior on the Lotka-Volterra predation. We assume that the individuals have many activities in a day for example. Each population is subdivided into subpopulations corresponding to different activities. In order to be clear, I have chosen the case of two activities for each population. We assume that the activities change is faster than the other processes (reproduction, mortality, predation…). This means that we consider population in which the individuals change their activities many times in a day while the reproduction and the predation effects are sensible after about ten days, for example. We use the aggregation method developed in [1] to obtain the global dynamics. Indeed, we start with a micro-model governing the micro-variables, which are the subpopulation densities; the aggregation method permits us to obtain a simpler system governing the macro-variables, which are the global population densities. Furthermore, this method allows us to observe emergence of the dynamics. Indeed, the method implies that the dynamics of the micro-system is close to an invariant manifold after a short time. We show that the dynamics on this manifold is a perturbation of the well-known center of the Lotka-Volterra model. Finally, we prove that a weak change of behavior can lead to a subcritical Hopf bifurcation in the global dynamics.     

Communication and Collective Consensus Making in?Animal Groups via Mechanical Interactions

Mechanical constraints have a strong influence on the dynamics and structure of granular aggregations. The contact forces within dense suspensions of active particles may give rise to intriguing phenomena, including anomalous density fluctuations, long-range orientational ordering, and spontaneous pattern formation. Various authors have proposed that these physical phenomena contribute to the ability of animal groups to move coherently. Our systematic numerical simulations confirm that spontaneous interactions of elongated individuals can trigger oriented motion in small groups. They are, however, insufficient in larger ones, despite their significant imprint on the group’s internal structure. It is also demonstrated that preferred directions of motion of a minority of group members can be communicated to others solely by mechanical interactions. These findings strengthen the link between pattern formation in active nematics and the collective decision making of social animals.     

No place like home: Opinion formation with homophily and implications for policy decisions

We set up an opinion diffusion model with a local opinion leader, and using simulations we show the possibility of driving a significant wedge between the opinions of two groups that exhibit homophily although individuals are highly conformist. There exists an opinion gap between the group to which the opinion leader belongs and the other group. This opinion gap increases according to the relative size of the residence community. We show empirical traits related to our simulation: Employing Swiss national referenda data from 2008 to 2012, we show that members of parliament match referenda outcomes in their residence communities closer than they do in neighboring communities and that this wedge interacts significantly with the relative size of the residence community.     

Local and global stability analysis of a two prey one predator model with help

In this paper we propose and study a three dimensional continuous time dynamical system modelling a three team consists of two preys and one predator with the assumption that during predation the members of both teams of preys help each other and the rate of predation of both teams are different. In this work we establish the local asymptotic stability of various equilibrium points to understand the dynamics of the model system. Different conditions for the coexistence of equilibrium solutions are discussed. Persistence, permanence of the system and global stability of the positive interior equilibrium solution are discussed by constructing suitable Lyapunov functional. At the end, numerical simulations are performed to substantiate our analytical findings.     

Interpersonal success factors for strategy implementation: a case study using group model building

Strategy implementation has been identified as an area of system dynamics literature requiring greater attention. Most strategies fail to be implemented successfully, and processes for effectively implementing strategy are yet to be fully explained and explored. The reported interpersonal success factors for strategy implementation are reported outcomes for group model building, suggesting potential applicability. A case study using validated survey methods yielded promising results, and suggests that further study is needed. This application of group model building may be a manifestation of the IKEA affect, where individuals value more highly solutions that they have partially assembled, and competency motivation, where individuals have positive affect to the successful completion of a complex task.     

A two-phase algorithm for consensus building in AHP-group decision making

Group decision making through the AHP has received significant attention in contemporary research, the primary focus of which has been on the issues of consistency and consensus building. In this paper, we concentrate on the latter and present a two-phase algorithm based on the optimal clustering of decision makers (members of a group) into sub groups followed by consensus building both within sub groups and between sub groups. Two-dimensional Sammon’s mapping is proposed as a tool for generating an approximate visualization of sub groups identified in multidimensional vector space, while the consensus convergence model is suggested for reaching agreement amongst individuals in and between sub groups. As a given, all decision makers evaluate the same decision elements within the AHP framework and produce individual scores of these decision elements. The consensual scores are obtained through the iterative procedure and the final scores are declared as the group decision. The results of two selected numerical examples are compared with two sets of results: the results obtained by the commonly used geometric mean aggregation method and also the results obtained if the consensus convergence model is applied directly without the prior clustering of the decision makers. The comparisons indicated the expected differences among the aggregation schemes and the final group scores. The matrices of respect values in the consensus convergence model, obtained for cases when the decision makers are optimally clustered and when they are not, show that in the latter case the decision makers receive lower weights of respect from other members in the group. Various tests showed that our approach is efficient in cases when no clusters can be visually and undoubtedly identified, especially if the number of group members is high.     

Global attractivity of nonautonomous stage-structured population models with dispersal and harvest

The nonautonomous stage-structured single-species dispersal model with harvesting of mature individuals in an N-patch environment is considered, in which the individual members of the population have a life history that takes them through two stages, immature and mature. By using the theory of monotone and concave operators to functional differential equations, we establish conditions under which this population dynamical system admits a positive periodic solution which attracts all positive solutions.     

Dynamic models of segregation†

Some segregation results from the practices of organizations, some from specialized communication systems, some from correlation with a variable that is non‐random; and some results from the interplay of individual choices. This is an abstract study of the interactive dynamics of discriminatory individual choices. One model is a simulation in which individual members of two recognizable groups distribute themselves in neighborhoods defined by reference to their own locations. A second model is analytic and deals with compartmented space. A final section applies the analytics to ‘neighborhood tipping.’ The systemic effects are found to be overwhelming: there is no simple correspondence of individual incentive to collective results. Exaggerated separation and patterning result from the dynamics of movement. Inferences about individual motives can usually not be drawn from aggregate patterns. Some unexpected phenomena, like density and vacancy, are generated. A general theory of ‘tipping’ begins to emerge.     

Optimal Bang-Bang Controls for a Two-Compartment Model in Cancer Chemotherapy

A class of mathematical models for cancer chemotherapy which have been described in the literature take the form of an optimal control problem over a finite horizon with control constraints and dynamics given by a bilinear system. In this paper, we analyze a two-dimensional model in which the cell cycle is broken into two compartments. The cytostatic agent used as control to kill the cancer cells is active only in the second compartment where cell division occurs and the cumulative effect of the drug is used to model the negative effect of the treatment on healthy cells. It is shown that singular controls are not optimal for this model and the optimality properties of bang-bang controls are established. Specifically, transversality conditions at the switching surfaces are derived. In a nondegenerate setting, these conditions guarantee the local optimality of the flow if satisfied, while trajectories will be no longer optimal if they are violated.     

Can topology reshape segregation patterns?

We consider a metapopulation version of the Schelling model of segregation over several complex networks and lattices. We show that the segregation process is topology independent and hence it is intrinsic to the individual tolerance. The role of the topology is to fix the places where the segregation patterns emerge. In addition we address the question of the time evolution of the segregation clusters, resulting from different dynamical regimes of a coarsening process, as a function of the tolerance parameter. We show that the underlying topology may alter the early stage of the coarsening process, once large values of the tolerance are used, while for lower ones a different mechanism is at work and it results to be topology independent.     

Motion equations of cooperative multi flexible mobile manipulator via recursive Gibbs–Appell formulation

In this paper, the developed model of an N-flexible-link mobile manipulator with revolute-prismatic joints is presented for the cooperative flexible multi mobile manipulator. In this model, the deformation of flexible links is calculated by using the assumed modes method. In additions, non-holonomic constraints of the robots’ mobile platforms that bound its locomotion are considered. This limitation is alleviated through the concurrent motion of revolute and prismatic joints, although it results in computational complexity and changes the final motion equations to time-varying form. Not only is the proposed dynamic model implemented for the multi-mobile manipulators with arms having independent motion, but also for multi-mobile manipulators in cooperation after defining gripper's kinematic constraints. These constraints are imported to the dynamic equations by defining Lagrange multipliers. The recursive Gibbs–Appell formulation is preferred over other similar approaches owing to the capability of solving the equations without the need to use Lagrange multipliers for eliminating non-holonomic constraints in addition to the novel optimized process of obtaining system equations. Hence, cumbersome simultaneous computations for eliminating the constraints of platform and arms are circumvented. Therefore, this formulation is improved for the first time by importing Lagrange multipliers for solving kinematic constrained systems. In the simulation section, the results of forward dynamics solution for two flexible single-arm manipulators with revolute-prismatic joints while carrying a rigid object are presented. Inverse dynamics equations of the system are also presented to obtain the maximum dynamic load-carrying capacity of the two-rigid-link mobile manipulators on a predefined path. Two constraints, namely the capacity of joint motors torque and robot motion stability are considered as the limitation criteria. The concluded motion equations are used to accurately control the movement of sensitive bodies, which is not achievable through the use of one platform.     

Survey study and experimental investigation on the local behavior of pedestrian groups

Current research on pedestrian dynamics mainly focuses on the interactions among isolated individuals, the impact of the presence of groups is not fully considered. In recent 5 years, researchers have started to investigate pedestrian group movement. The aim of this work is to explore the local behavior of pedestrian groups by questionnaires and field observation. Survey study focused on pedestrians' psychology when walking in groups, which included five parts: group size, interpersonal distance, spatial relationship among group members, speed adjustment of group members, information transmission, and acid action among group members. Meantime a field observation was carried out to study group movement characteristics, which contained speed, step frequency, offset angle and interpersonal distance. The survey results show that group members have a closer interpersonal distance, faster information transmission and plenty of acid action. Conversely, group walking has a negative influence on pedestrian's speed, step frequency by comparing with the way isolated pedestrian walks. In addition, it is found that for a certain group, the group members are able to keep movement consistent. Also there exists obvious movement diversity among different group types (male dyads, female dyads, couple groups, and ordinary‐friend groups) because of different gender and social relationship. Ultimately the results will be more promising for helping to model the movement of pedestrian groups. © 2014 Wiley Periodicals, Inc. Complexity 20: 87–97, 2015     

The evolution of cooperation in spatial groups

Much of human cooperation remains an evolutionary riddle. There is evidence that individuals are often organized into groups in many social situations. Inspired by this observation, we propose a simple model of evolutionary public goods games in which individuals are organized into networked groups. Here, nodes in the network represent groups; the edges, connecting the nodes, refer to the interactions between the groups. Individuals establish public goods games with partners in the same group and migrate among neighboring groups depending on their payoffs and expectations. We show that the paradigmatic public goods social dilemma can be resolved and high cooperation levels are attained in structured groups, even in relatively harsh conditions for cooperation. Further, by means of numerical simulations and mean-field analysis, we arrive at the result: larger average group size and milder cooperation environment would lead to lower cooperation level but higher average payoffs of the entire population. Altogether, these results emphasize that our understanding of cooperation can be enhanced by investigations of how spatial groups of individuals affect the evolution dynamics, which might help in explaining the emergence and evolution of cooperation.