Enrique Burgos

Why nestedness in mutualistic networks

We investigate the relationship between the nested organization of mutualistic systems and their robustness against the extinction of species. We establish that a nested pattern of contacts is the best possible one as far as robustness is concerned, but only when the least linked species have the greater probability of becoming extinct. We introduce a coefficient that provides a quantitative measure of the robustness of a mutualistic system.

Analysis and assembling of network structure in mutualistic systems.

It has been observed that mutualistic bipartite networks have a nested structure of interactions. In addition, the degree distributions associated with the two guilds involved in such networks (e.g., plants and pollinators or plants and seed dispersers) approximately follow a truncated power law (TPL). We show that nestedness and TPL distributions are intimately linked, and that any biological reasons for such truncation are superimposed to finite size effects. We further explore the internal organization of bipartite networks by developing a self-organizing network model (SNM) that reproduces empirical observations of pollination systems of widely different sizes. Since the only inputs to the SNM are numbers of plant and animal species, and their interactions (i.e., no data on local abundance of the interacting species are needed), we suggest that the well-known association between species frequency of interaction and species degree is a consequence rather than a cause, of the observed network structure.

Self organization in a minority game: the rôle of memory and a probabilistic approach

A minority game whose strategies are given by probabilities p, is replaced by a ‘simplified’ version that makes no use of memories at all. Numerical results show that the corresponding distribution functions are indistinguishable. A related approach, using a random walk formulation, allows us to identify the origin of correlations and self-organization in the model, and to understand their disappearance for a different strategys update rule, as pointed out in a previous work.

Two classes of bipartite networks: nested biological and social systems.

Bipartite graphs have received some attention in the study of social networks and of biological mutualistic systems. A generalization of a previous model is presented, that evolves the topology of the graph in order to optimally account for a given contact preference rule between the two guilds of the network. As a result, social and biological graphs are classified as belonging to two clearly different classes. Projected graphs, linking the agents of only one guild, are obtained from the original bipartite graph. The corresponding evolution of its statistical properties is also studied. An example of a biological mutualistic network is analyzed in detail, and it is found that the model provides a very good fitting of all the main statistical features. The model also provides a proper qualitative description of the same features observed in social webs, suggesting the possible reasons underlying the difference in the organization of these two kinds of bipartite networks.

Thermal treatment of the minority game.

We study a cost function for the aggregate behavior of all the agents involved in the minority game (MG) or the bar attendance model (BAM). The cost function allows us to define a deterministic, synchronous dynamic that yields results that have the main relevant features than those of the probabilistic, sequential dynamics used for the MG or the BAM. We define a temperature through a Langevin approach in terms of the fluctuations of the average attendance. We prove that the cost function is an extensive quantity that can play the role of an internal energy of the many-agent system while the temperature so defined is an intensive parameter. We compare the results of the thermal perturbation to the deterministic dynamics and prove that they agree with those obtained with the MG or BAM in the limit of very low temperature.

Order and disorder in the local evolutionary minority game

We study a modification of the Evolutionary Minority Game (EMG) in which agents are placed in the nodes of a regular or a random graph. A neighborhood for each agent can thus be defined and a modification of the usual relaxation dynamics can be made in which each agent updates her decision scheme depending upon the options made in her immediate neighborhood. We name this model the Local Evolutionary Minority Game (LEMG). We report numerical results for the topologies of a ring, a torus and a random graph changing the size of the neighborhood. We focus our discussion in a one-dimensional system and perform a detailed comparison of the results obtained from the random relaxation dynamics of the LEMG and from a linear chain of interacting spin-like variables with temperature. We provide a physical interpretation of the surprising result that in the LEMG a better coordination (a lower frustration) is achieved if agents base their actions on local information. We show how the LEMG can be regarded as a model that gradually interpolates between a fully ordered, antiferromagnetic-like system, and a fully disordered system that can be assimilated to a spin glass.

Multiparticle reactions with spatial anisotropy

We study the effect of anisotropic diffusion on the one-dimensional annihilation reaction kA\ensuremath{\rightarrow}inert with partial reaction probabilities when hard-core particles meet in groups of k nearest neighbors. Based on scaling arguments, mean-field approaches, and random-walk considerations, we argue that the spatial anisotropy introduces no appreciable changes as compared to the isotropic case. Our conjectures are supported by numerical simulations for slow reaction rates, for k=2 and 4.

Comment on "Self-segregation versus clustering in the evolutionary minority game".

This is a comment on a paper by S. Hod and E. Nakar, published in Phys. Rev. Lett. 88, 238702 (2002)

Quenching and annealing in the minority game

We study the bar attendance model (BAM) and a generalized version of the minority game (MG) in which a number of agents self organize to match an attendance that is fixed externally as a control parameter. We compare the probabilistic dynamics used in the MG with one that we introduce for the BAM that makes better use of the same available information. The relaxation dynamics of the MG leads the system to long lived, metastable (quenched) configurations in which adaptive evolution stops in spite of being far from equilibrium. On the contrary, the BAM relaxation dynamics avoids the MG glassy state, leading to an equilibrium configuration. Finally, we introduce in the MG model the concept of annealing by defining a new procedure with which one can gradually overcome the metastable MG states, bringing the system to an equilibrium that coincides with the one obtained with the BAM.

Understanding and characterizing nestedness in mutualistic bipartite networks

In this work we present a dynamical model that successfully describes the organization of mutualistic ecological systems. The main characteristic of these systems is the nested structure of the bipartite adjacency matrix describing their interactions. We introduce a nestedness coefficient, as an alternative to the Atmar and Patterson temperature, commonly used to measure the nestedness degree of the network. This coefficient has the advantage of being based on the robustness of the ecological system and it is not only describing the ordering of the bipartite matrix but it is also able to tell the difference, if any, between the degree of organization of each guild.