Models for pheromone evaluation in Ant Systems for Mobile Ad-hoc networks

On a mobile ad-hoc network environment, where the resources are scarce, the knowledge about the network's link state is essential to optimize the routing procedures. This paper presents a study about different pheromone evaluation models and how they react to possible changes in traffic rate. Observing how the pheromone value on a link changes, it could be possible to identify certain patterns which can indicate the path status. For this study, the behavior of the Ant System evaluation model was compared with a Temporal Active Pheromone model (a biological approach) and a Progressive Pheromone Reduction model with and without a maximum pheromone limit.

Adaptive approach heuristics for the generalized assignment problem

The Generalized Assignment Problem consists in assigning a setof tasks to a set of agents with minimum cost. Each agent hasa limited amount of a single resource and each task must beassigned to one and only one agent, requiring a certain amountof the resource of the agent. We present new metaheuristics forthe generalized assignment problem based on hybrid approaches.One metaheuristic is a MAX-MIN Ant System (MMAS), an improvedversion of the Ant System, which was recently proposed byStutzle and Hoos to combinatorial optimization problems, and itcan be seen has an adaptive sampling algorithm that takes inconsideration the experience gathered in earlier iterations ofthe algorithm. Moreover, the latter heuristic is combined withlocal search and tabu search heuristics to improve the search.A greedy randomized adaptive search heuristic (GRASP) is alsoproposed. Several neighborhoods are studied, including one basedon ejection chains that produces good moves withoutincreasing the computational effort. We present computationalresults of the comparative performance, followed by concludingremarks and ideas on future research in generalized assignmentrelated problems.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Hybrid fault diagnosis scheme implementation for power distribution systems automation

Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

Optimization of the Topology of Electric Energy Distribution Networks by Using Algorithm Inspired on Ant Behaviors

An algorithm inspired on ant behavior is developed in order to find out the topology of an electric energy distribution network with minimum power loss. The algorithm performance is investigated in hypothetical and actual circuits. When applied in an actual distribution system of a region of the State of Sao Paulo (Brazil), the solution found by the algorithm presents loss lower than the topology built by the concessionary company.

Interaction between forest fragments and adjacent coffee and pasture agroecosystems: responses of the ant communities (Hymenoptera, Formicidae)

The responses of the ant community to environmental change, from forest fragment to agroecosystems (coffee or pasture) were evaluated in the south of the state of Minas Gerais, Brazil. In this paper we analized the interactions between forest and the two most typical agroecosystem from southest Brazil: sun-growing coffee plantation and introduced pasture. We sampled the ant community from five of each agroecosystems, inside the adjacent forest fragment, and on the edge between them. In each site we removed the litter from fifteen 1m(2) plots and extracted the ants using a Winkler extractor. A total of 165 ant species, distributed in 48 genera and 10 subfamilies were recorded. The coffee plantation presented the lowest abundance and estimated species richness. The causes of the changes observed among the areas are discussed.

Ant genomics sheds light on the molecular regulation of social organization.

Ants are powerful model systems for the study of cooperation and sociality. In this review, we discuss how recent advances in ant genomics have contributed to our understanding of the evolution and organization of insect societies at the molecular level.

Sociogenomics of Cooperation and Conflict during Colony Founding in the Fire Ant Solenopsis invicta.

One of the fundamental questions in biology is how cooperative and altruistic behaviors evolved. The majority of studies seeking to identify the genes regulating these behaviors have been performed in systems where behavioral and physiological differences are relatively fixed, such as in the honey bee. During colony founding in the monogyne (one queen per colony) social form of the fire ant Solenopsis invicta, newly-mated queens may start new colonies either individually (haplometrosis) or in groups (pleometrosis). However, only one queen (the "winner") in pleometrotic associations survives and takes the lead of the young colony while the others (the "losers") are executed. Thus, colony founding in fire ants provides an excellent system in which to examine the genes underpinning cooperative behavior and how the social environment shapes the expression of these genes. We developed a new whole genome microarray platform for S. invicta to characterize the gene expression patterns associated with colony founding behavior. First, we compared haplometrotic queens, pleometrotic winners and pleometrotic losers. Second, we manipulated pleometrotic couples in order to switch or maintain the social ranks of the two cofoundresses. Haplometrotic and pleometrotic queens differed in the expression of genes involved in stress response, aging, immunity, reproduction and lipid biosynthesis. Smaller sets of genes were differentially expressed between winners and losers. In the second experiment, switching social rank had a much greater impact on gene expression patterns than the initial/final rank. Expression differences for several candidate genes involved in key biological processes were confirmed using qRT-PCR. Our findings indicate that, in S. invicta, social environment plays a major role in the determination of the patterns of gene expression, while the queen's physiological state is secondary. These results highlight the powerful influence of social environment on regulation of the genomic state, physiology and ultimately, social behavior of animals.

Genetic clusters and sex-biased gene flow in a unicolonial Formica ant.

BACKGROUND: Animal societies are diverse, ranging from small family-based groups to extraordinarily large social networks in which many unrelated individuals interact. At the extreme of this continuum, some ant species form unicolonial populations in which workers and queens can move among multiple interconnected nests without eliciting aggression. Although unicoloniality has been mostly studied in invasive ants, it also occurs in some native non-invasive species. Unicoloniality is commonly associated with very high queen number, which may result in levels of relatedness among nestmates being so low as to raise the question of the maintenance of altruism by kin selection in such systems. However, the actual relatedness among cooperating individuals critically depends on effective dispersal and the ensuing pattern of genetic structuring. In order to better understand the evolution of unicoloniality in native non-invasive ants, we investigated the fine-scale population genetic structure and gene flow in three unicolonial populations of the wood ant F. paralugubris. RESULTS: The analysis of geo-referenced microsatellite genotypes and mitochondrial haplotypes revealed the presence of cryptic clusters of genetically-differentiated nests in the three populations of F. paralugubris. Because of this spatial genetic heterogeneity, members of the same clusters were moderately but significantly related. The comparison of nuclear (microsatellite) and mitochondrial differentiation indicated that effective gene flow was male-biased in all populations. CONCLUSION: The three unicolonial populations exhibited male-biased and mostly local gene flow. The high number of queens per nest, exchanges among neighbouring nests and restricted long-distance gene flow resulted in large clusters of genetically similar nests. The positive relatedness among clustermates suggests that kin selection may still contribute to the maintenance of altruism in unicolonial populations if competition occurs among clusters.

The genomic impact of 100 million years of social evolution in seven ant species.

Ants (Hymenoptera, Formicidae) represent one of the most successful eusocial taxa in terms of both their geographic distribution and species number. The publication of seven ant genomes within the past year was a quantum leap for socio- and ant genomics. The diversity of social organization in ants makes them excellent model organisms to study the evolution of social systems. Comparing the ant genomes with those of the honeybee, a lineage that evolved eusociality independently from ants, and solitary insects suggests that there are significant differences in key aspects of genome organization between social and solitary insects, as well as among ant species. Altogether, these seven ant genomes open exciting new research avenues and opportunities for understanding the genetic basis and regulation of social species, and adaptive complex systems in general.

Inbreeding and sex-biased gene flow in the ant Formica exsecta.

The objective of this study was to assess breeding and dispersal patterns of both males and females in a monogyne (a single queen per colony) population of ants. Monogyny is commonly associated with extensive nuptial flights, presumably leading to considerable gene flow over large areas. Opposite to these expectations we found evidence of both inbreeding and sex-biased gene flow in a monogyne population of Formica exsecta. We found a significant degree of population subdivision at a local scale (within islands) for queens (females heading established colonies) and workers, but not for colony fathers (the males mated to the colony queens). However, we found little evidence of population subdivision at a larger scale (among islands). More conclusive support for sex-biased gene flow comes from the analysis of isolation by distance on the largest island, and from assignment tests revealing differences in female and male philopatry. The genetic similarity between pairs of queens decreased significantly when geographical distance increased, demonstrating limited dispersal and isolation by distance in queens. By contrast, we found no such pattern for colony fathers. Furthermore, a significantly greater fraction of colony queens were assigned as having originated from the population of residence, as compared to colony fathers. Inbreeding coefficients were significantly positive for workers, but not for mother queens. The queen-male relatedness coefficient of 0.23 (regression relatedness) indicates that mating occurs between fairly close relatives. These results suggest that some monogyne species of ants have complex dispersal and mating systems that can result in genetic isolation by distance over small geographical scales. More generally, this study also highlights the importance of identifying the relevant scale in analyses of population structure and dispersal.

Patterns of positive selection in seven ant genomes.

The evolution of ants is marked by remarkable adaptations that allowed the development of very complex social systems. To identify how ant-specific adaptations are associated with patterns of molecular evolution, we searched for signs of positive selection on amino-acid changes in proteins. We identified 24 functional categories of genes which were enriched for positively selected genes in the ant lineage. We also reanalyzed genome-wide data sets in bees and flies with the same methodology to check whether positive selection was specific to ants or also present in other insects. Notably, genes implicated in immunity were enriched for positively selected genes in the three lineages, ruling out the hypothesis that the evolution of hygienic behaviors in social insects caused a major relaxation of selective pressure on immune genes. Our scan also indicated that genes implicated in neurogenesis and olfaction started to undergo increased positive selection before the evolution of sociality in Hymenoptera. Finally, the comparison between these three lineages allowed us to pinpoint molecular evolution patterns that were specific to the ant lineage. In particular, there was ant-specific recurrent positive selection on genes with mitochondrial functions, suggesting that mitochondrial activity was improved during the evolution of this lineage. This might have been an important step toward the evolution of extreme lifespan that is a hallmark of ants.

Variable queen number in ant colonies: no impact on queen turnover, inbreeding, and population genetic differentiation in the ant Formica selysi.

Variation in queen number alters the genetic structure of social insect colonies, which in turn affects patterns of kin-selected conflict and cooperation. Theory suggests that shifts from single- to multiple-queen colonies are often associated with other changes in the breeding system, such as higher queen turnover, more local mating, and restricted dispersal. These changes may restrict gene flow between the two types of colonies and it has been suggested that this might ultimately lead to sympatric speciation. We performed a detailed microsatellite analysis of a large population of the ant Formica selysi, which revealed extensive variation in social structure, with 71 colonies headed by a single queen and 41 by multiple queens. This polymorphism in social structure appeared stable over time, since little change in the number of queens per colony was detected over a five-year period. Apart from queen number, single- and multiple-queen colonies had very similar breeding systems. Queen turnover was absent or very low in both types of colonies. Single- and multiple-queen colonies exhibited very small but significant levels of inbreeding, which indicates a slight deviation from random mating at a local scale and suggests that a small proportion of queens mate with related males. For both types of colonies, there was very little genetic structuring above the level of the nest, with no sign of isolation by distance. These similarities in the breeding systems were associated with a complete lack of genetic differentiation between single- and multiple-queen colonies, which provides no support for the hypothesis that change in queen number leads to restricted gene flow between social forms. Overall, this study suggests that the higher rates of queen turnover, local mating, and population structuring that are often associated with multiple-queen colonies do not appear when single- and multiple-queen colonies still coexist within the same population, but build up over time in populations consisting mostly of multiple-queen colonies.

Systems medicine and integrated care to combat chronic noncommunicable diseases

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.