El modelo de desarrollo con inclusión y su inserción en la multipolaridad: Agendas y geopolíticas en conflicto

Durante los últimos diez años, la Argentina y la región encararon un cambio paradigmático.1 Esto se produce en primer lugar a nivel de modelo de acumulación o de desarrollo, y por tanto del rol del Estado en relación con la economía y la sociedad. La crisis del modelo neoliberal generó una praxis concretada en otro rol del Estado y políticas públicas, y una concepción original sobre la resolución de la crisis de endeudamiento impuesta por la financiación de la economía. Un enfoque analítico en el cual confluyen matrices nacional-populares, neodesarrollistas, progresistas y de izquierda latinoamericana que terminan por perfilar un modelo de desarrollo con inclusión social.Fil: Garcia Delgado, Daniel Reynaldo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Facultad Latinoamericana de Ciencias Sociales; Argentin

Consensus of self-driven agents with avoidance of collisions

In recent years, many efforts have been addressed on collision avoidance of collectively moving agents. In this paper, we propose a modified version of the Vicsek model with adaptive speed, which can guarantee the absence of collisions. However, this strategy leads to an aggregated state with slowly moving agents. We therefore further introduce a certain repulsion, which results in both faster consensus and longer safe distance among agents, and thus provides a powerful mechanism for collective motions in biological and technological multi-agent systems.Comment: 8 figures, and 7 page

Inherent noise can facilitate coherence in collective swarm motion

Among the most striking aspects of the movement of many animal groups are their sudden coherent changes in direction. Recent observations of locusts and starlings have shown that this directional switching is an intrinsic property of their motion. Similar direction switches are seen in self-propelled particle and other models of group motion. Comprehending the factors that determine such switches is key to understanding the movement of these groups. Here, we adopt a coarse-grained approach to the study of directional switching in a self-propelled particle model assuming an underlying one-dimensional Fokker–Planck equation for the mean velocity of the particles. We continue with this assumption in analyzing experimental data on locusts and use a similar systematic Fokker–Planck equation coefficient estimation approach to extract the relevant information for the assumed Fokker–Planck equation underlying that experimental data. In the experiment itself the motion of groups of 5 to 100 locust nymphs was investigated in a homogeneous laboratory environment, helping us to establish the intrinsic dynamics of locust marching bands. We determine the mean time between direction switches as a function of group density for the experimental data and the self-propelled particle model. This systematic approach allows us to identify key differences between the experimental data and the model, revealing that individual locusts appear to increase the randomness of their movements in response to a loss of alignment by the group. We give a quantitative description of how locusts use noise to maintain swarm alignment. We discuss further how properties of individual animal behavior, inferred by using the Fokker–Planck equation coefficient estimation approach, can be implemented in the self-propelled particle model to replicate qualitatively the group level dynamics seen in the experimental data

Traffic Instabilities in Self-Organized Pedestrian Crowds

In human crowds as well as in many animal societies, local interactions among individuals often give rise to self-organized collective organizations that offer functional benefits to the group. For instance, flows of pedestrians moving in opposite directions spontaneously segregate into lanes of uniform walking directions. This phenomenon is often referred to as a smart collective pattern, as it increases the traffic efficiency with no need of external control. However, the functional benefits of this emergent organization have never been experimentally measured, and the underlying behavioral mechanisms are poorly understood. In this work, we have studied this phenomenon under controlled laboratory conditions. We found that the traffic segregation exhibits structural instabilities characterized by the alternation of organized and disorganized states, where the lifetime of well-organized clusters of pedestrians follow a stretched exponential relaxation process. Further analysis show that the inter-pedestrian variability of comfortable walking speeds is a key variable at the origin of the observed traffic perturbations. We show that the collective benefit of the emerging pattern is maximized when all pedestrians walk at the average speed of the group. In practice, however, local interactions between slow- and fast-walking pedestrians trigger global breakdowns of organization, which reduce the collective and the individual payoff provided by the traffic segregation. This work is a step ahead toward the understanding of traffic self-organization in crowds, which turns out to be modulated by complex behavioral mechanisms that do not always maximize the group's benefits. The quantitative understanding of crowd behaviors opens the way for designing bottom-up management strategies bound to promote the emergence of efficient collective behaviors in crowds.Comment: Article published in PLoS Computational biology. Freely available here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.100244

Collective Animal Behavior from Bayesian Estimation and Probability Matching

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is based on empirical fits to observations and we lack first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching.
In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability given by the Bayesian estimation that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior

The effects of parasitism and body length on positioning within wild fish shoals

The influence of body length and parasitism on the positioning behaviour of individuals in wild fish shoals was investigated by a novel means of capturing entire shoals of the banded killifish (Fundulus diaphanus, Lesueur) using a grid-net that maintained the two-dimensional positions of individuals within shoals. Fish in the front section of a shoal were larger than those in the rear. Individuals parasitized by the digenean trematode (Crassiphiala bulboglossa, Haitsma) showed a tendency to occupy the front of shoals. Parasitized fish were also found more in peripheral positions than central ones in a significant number of shoals. Shoal geometry was affected by the overall parasite prevalence of shoal members; shoals with high parasite prevalence displayed increasingly phallanx-like shoal formations, whereas shoals with low prevalence were more elliptical. There was no relationship between body length and parasite abundance or prevalence in the fish population which suggests body length and parasite status are independent predictors of positioning behaviour. Solitary individuals found outside shoals were both more likely to be parasitized and had higher parasite abundance than individuals engaged in shoaling. Differences in the shoaling behaviour of parasitized and unparasitized fish are discussed in the context of the adaptive manipulation hypothesis

Effects of anisotropic interactions on the structure of animal groups

This paper proposes an agent-based model which reproduces different structures of animal groups. The shape and structure of the group is the effect of simple interaction rules among individuals: each animal deploys itself depending on the position of a limited number of close group mates. The proposed model is shown to produce clustered formations, as well as lines and V-like formations. The key factors which trigger the onset of different patterns are argued to be the relative strength of attraction and repulsion forces and, most important, the anisotropy in their application.Comment: 22 pages, 9 figures. Submitted. v1-v4: revised presentation; extended simulations; included technical results. v5: added a few clarification

Differences in Nutrient Requirements Imply a Non-Linear Emergence of Leaders in Animal Groups

Collective decision making and especially leadership in groups are among the most studied topics in natural, social, and political sciences. Previous studies have shown that some individuals are more likely to be leaders because of their social power or the pertinent information they possess. One challenge for all group members, however, is to satisfy their needs. In many situations, we do not yet know how individuals within groups distribute leadership decisions between themselves in order to satisfy time-varying individual requirements. To gain insight into this problem, we build a dynamic model where group members have to satisfy different needs but are not aware of each other's needs. Data about needs of animals come from real data observed in macaques. Several studies showed that a collective movement may be initiated by a single individual. This individual may be the dominant one, the oldest one, but also the one having the highest physiological needs. In our model, the individual with the lowest reserve initiates movements and decides for all its conspecifics. This simple rule leads to a viable decision-making system where all individuals may lead the group at one moment and thus suit their requirements. However, a single individual becomes the leader in 38% to 95% of cases and the leadership is unequally (according to an exponential law) distributed according to the heterogeneity of needs in the group. The results showed that this non-linearity emerges when one group member reaches physiological requirements, mainly the nutrient ones – protein, energy and water depending on weight - superior to those of its conspecifics. This amplification may explain why some leaders could appear in animal groups without any despotism, complex signalling, or developed cognitive ability

Copycat dynamics in leaderless animal group navigation

Background: Many animals are known to have improved navigational efficiency when moving together as a social group. One potential mechanism for social group navigation is known as the 'many wrongs principle', where information from many inaccurate compasses is pooled across the group. In order to understand how animal groups may use the many wrongs principle to navigate, it is important to consider how directional information is transferred and shared within the group. Methods: Here we use an individual-based model to explore the information-sharing and copying dynamics of a leaderless animal group navigating towards a target in a virtual environment. We assume that communication and information-sharing is indirect and arises through individuals partially copying the movement direction of their neighbours and weighting this information relative to their individual navigational knowledge. Results: We find that the best group navigation performance occurs when individuals directly copy the direction of movement of a subset of their neighbours while only giving a small (6%) weighting to their individual navigational knowledge. Surprisingly, such a strategy is shown to be highly efficient regardless of the level of individual navigational error. We find there is little relative improvement in navigational efficiency when individuals copy from more than 7 influential neighbours. Conclusions: Our findings suggest that we would expect navigating group-living animals to predominantly copy the movement of others rather than relying on their own navigational knowledge. We discuss our results in the context of individual and group navigation behaviour in animals