Flujos informacionales en repositorios cooperativos : Consideraciones sobre algunas experiencias en instituciones académicas de América Latina

Este trabajo, de tipo descriptivo exploratorio, se propone efectuar un análisis de una serie de repositorios cooperativos pertenecientes a instituciones académicas de América Latina. Hace hincapié en la importancia de la cooperación como práctica de larga data en el ámbito de las bibliotecas, muchas de las cuales se han convertido en líderes o partícipes importantes tanto en la implementación como en el desarrollo de los repositorios en sus respectivas instituciones. Se toman en consideración los flujos informacionales que los atraviesan a fin de conocer cómo se delinean y desarrollan en el marco de instituciones académicas de cierta envergadura y complejidad, a través de un análisis de documentación. Se resaltan los modelos de flujos de información detectados en dichos repositorios cooperativos y cómo estos, desde su singularidad, favorecen la visibilidad y la difusión del conocimiento académico y científico existente en formato digital

Flujos informacionales en repositorios cooperativos : Consideraciones sobre algunas experiencias en instituciones académicas de América Latina

Este trabajo, de tipo descriptivo exploratorio, se propone efectuar un análisis de una serie de repositorios cooperativos pertenecientes a instituciones académicas de América Latina. Hace hincapié en la importancia de la cooperación como práctica de larga data en el ámbito de las bibliotecas, muchas de las cuales se han convertido en líderes o partícipes importantes tanto en la implementación como en el desarrollo de los repositorios en sus respectivas instituciones. Se toman en consideración los flujos informacionales que los atraviesan a fin de conocer cómo se delinean y desarrollan en el marco de instituciones académicas de cierta envergadura y complejidad, a través de un análisis de documentación. Se resaltan los modelos de flujos de información detectados en dichos repositorios cooperativos y cómo estos, desde su singularidad, favorecen la visibilidad y la difusión del conocimiento académico y científico existente en formato digital

University Networking in Developing Countries based on C4D-Learning

In recent years, the establishment of cooperation networks between universities is one of the most important trends in higher education all over the world. Well recognized local and international university networks have been implemented in most educational institutions. It is common to find associations of various prestigious universities collaborating in a high-­‐technology research project including a very specialized teaching as well. This is the most common cooperation networks among higher education institutions in developed countries. An increasingly common type of networking between developed and developing universities is related to cooperation for development. This is the case of many universities in Africa that are needed for external help in order to improve its capabilities. Numerous memorandums of understanding regarding first world institutions that collaborate with universities in developing countries describe contributions of eventual visiting professors, teaching material and courses. But probably there exist another type of more important, but less explored association, such as networking among developing universities. The new goal, in this case, is not only the excellence but also the mutual development.

Dinâmicas de reprodução do comércio e os novos papéis urbanos de pequenas cidades norte-rio-grandenses: um olhar a partir das redes associativistas de supermercados

The work presented here aims to make an analysis of the socio-spatial dynamics of associative supermarket chains and their importance in redefining the roles of small urban North Rio Grande cities. The theoretical approach gives priority to business as a city constituent whose understanding allows us to seize the new socio-spatial dynamics of small towns in the face of globalization and which caused changes in the scope of its commercial forms. In this sense, we understand that trade, as an essentially urban activity has a very specific characteristic, with respect to its ability to transform the content and meaning of places. Another important factor in the construction work was the context of changes in the capitalist production system with the advent of flexible production and the determinations of the economic globalization process that brought new ways of organizing trade. The empirical analysis of the research includes two associative supermarket chains, the “Rede 10” and the “Rede Seridó”, bringing together basic elements for understanding the genesis and evolution of this new organizational model of trade in small towns of the state, as well as allowed -In understand the main changes in this segment of commercial activity. The methodology we used literature in books and periodicals, collected mainly secondary data collection with the SEBRAE and the ABRAS and was still a field research where interviews were conducted forwarded along to the associative network managers to supermarkets, owners of associated facilities and with consumers of the surveyed networks .Finally, we conclude that the formation and expansion of associative supermarket chains in the context of small cities potiguares is essentially in a survival alternative traditional small traders, that sharing the associative principles albeit somewhat rigidly guided by the training cooperation networks can not only stay in the market , but to impose as a new agent in the capital of the reproduction process. Thus, the associative supermarket chains in the search for new spaces, particularly within small towns end up promoting new momentum in these cities providing different flows and interconnections with different places, giving new content and urban roles. By taking not only the condition of the place of living, but also the place to reproduce the capital, small towns offer their population better able to make purchases, thus avoiding the mandatory population shifts to other urban centers in order to meet their consumption needs.

Preliminary study of cooperation in hybrid ad-hoc networks

In this paper, we present a first approach to evolve a cooperative behavior in ad hoc networks. Since wireless nodes are energy constrained, it may not be in the best interest of a node to always accept relay requests. On the other hand, if all nodes decide not to expend energy in relaying, then network throughput will drop dramatically. Both these extreme scenarios are unfavorable to the interests of a user. In this paper we deal with the issue of user cooperation in ad hoc networks by developing the algorithm called Generous Tit-For-Tat. We assume that nodes are rational, i.e., their actions are strictly determined by self-interest, and that each node is associated with a minimum lifetime constraint. Given these lifetime constraints and the assumption of rational behavior, we study the added behavior of the network.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

The rewards of cooperation: The effects of membership in European regulatory networks

Networks famously epitomize the shift from 'government' to 'governance' as governing structures for exercising control and coordination besides hierarchies and markets. Their distinctive features are their horizontality, the interdependence among member actors and an interactive decision-making style. Networks are expected to increase the problem-solving capacity of political systems in a context of growing social complexity, where political authority is increasingly fragmented across territorial and functional levels. However, very little attention has been given so far to another crucial implication of network governance - that is, the effects of networks on their members. To explore this important question, this article examines the effects of membership in European regulatory networks on two crucial attributes of member agencies, which are in charge of regulating finance, energy, telecommunications and competition: organisational growth and their regulatory powers. Panel analysis applied to data on 118 agencies during a ten-year period and semi-structured interviews provide mixed support regarding the expectation of organisational growth while strongly confirming the positive effect of networks on the increase of the regulatory powers attributed to member agencies.

A Forwarding Cooperation Protocol for Plain and Cluster-based Ad Hoc Networks

Peer-reviewed

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Particle Competition and Cooperation in Networks for Semi-Supervised Learning with Concept Drift

Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.