Universität und solidarische Ökonomie

RESUMO: A economia solidária é aqui apresentada como um movimento social emancipatório e como uma das formas de resistências das trabalhadoras e trabalhadores ao modelo de desenvolvimento capitalista. O movimento contemporâneo de economia solidária abrange o processo de produção, comercialização e finanças. A economia solidária é caracterizada pela posse coletiva dos meios de produção e pelo controle dos trabalhadores dos empreendimentos através de autogestão, cooperação e solidariedade. Os empreendimentos econômicos solidários se organizam sob a forma de cooperativas, associações e grupos informais. Um dos maiores desafios da economia solidária está no campo educativo, porque impõe a desconstrução dos princípios individualistas e privatistas preponderantes na maioria das relações econômicas, e exige a construção de outra cultura pautada na solidariedade. Nesse sentido, a pesquisa realizada, tem como objeto de estudo as metodologias de incubação fomentadas pelas universidades nas ações de economia solidária. Para isso, analisamos as experiências da Incubadora de Economia Solidária da Universidade Federal da Paraíba - Brasil e da Incubadora na Universidade de Kassel- Alemanha – Verein für Solidarische Ökonomie e.V. A pesquisa buscou conhecer e analisar as práticas de incubagem das universidades na economia solidária, como processos de mudança social. A coleta de informações foi realizada, tendo por base, uma revisão bibliográfica, relatórios das Incubadoras, registros fotográficos, observação participante e entrevistas semi-estruturadas. Os resultados da análise indicam que as metodologias de incubação na economia solidaria, por terem um caráter aberto e participativo, por considerarem os condicionamentos históricos e as diferentes culturas, fazem-nas portadoras de mudanças sociais. Esta metodologia pode ser utilizada por diferentes atores, em lugares e situações distintas. A pesquisa indica ainda, a centralidade da questão ecológica como elemento que poderá unificar o movimento internacional de economia solidária.

Nachhaltige Energie für ländliche Entwicklung in dem Sub-Sahara Afrika: interdisziplinäre Herangehensweise und organisatorische Herausforderung

Angesichts der Geschichte der Entwicklungspolitik, ist diese Arbeit darauf ausgerichtet, einige Beobachtungen in Bezug auf die so genannte Entwicklung hervorzuheben; insbesondere auf die andauernde prekäre Situation und Armut in ländlichen afrikanischen Gebieten. Armut ist nach Amartya SEN – weiter präzisiert von J.L. Dubois – die Deprivation von „Fähigkeiten“, die Individuen und lokale Gemeinschaften zu ausgeschlossenen und vergessenen Akteuren des Systems machen. Das nennt Paulo Freire, das Menschen zu „Objekten“ gemacht werden. Es rechtfertigt die starke Annahme, die in dieser Studie getroffen wird, dass vielmehr die Menschen als „Subjekte“ ihrer Veränderung und Entwicklung im Mittelpunkt stehen. Die Arbeit zeigt und erklärt in historischer Chronologie, wie die Entwicklungspolitiken und unterschiedliche Beteiligte auf allen Ebenen diese Situation verursachen. Trotz alledem bleiben die Individuen und lokalen Gemeinschaften, die in Symbiose mit ihrer natürlichen Umwelt leben, die reich an verschiedenen Ressourcen und Potentialen ist, als Reaktion darauf und gleichzeitig als Überlebensstrategie zutiefst verbunden mit dem, was sie vor Ort haben, womit sie eine tiefere und intensive Beziehung besitzen, wenn man von ihrer Geschichte, ihrer Kultur und der Handlungslogik ausgeht. Für externe Akteure, die sie über das vorhandene System dominieren und beeinflussen bleiben sie „Objekte“, aber in der Vielzahl ihrer endogenen Initiativen, zeigen sie die Fähigkeit und Substanz, die beweisen, dass sie auf ihrer Ebene das eigentliche Subjekt sind, die dynamischen Akteure. Aber isolierte Initiativen auf spezifische reale Bedürfnisse bei gleichzeitiger Dominierung durch das System mit seiner Marktlogik, führt dies langfristig nur zu dem Zirkulus Vitiosus der Armut. Daher ist eine ganzheitliche Sicht entscheidend für nachhaltige Entwicklung und für die notwendige Veränderung. Es geht nicht nur um die Veränderung des Systems und die Wahl politischer Maßnahmen, sondern genau genommen um das Verhalten der Akteure auf allen Ebenen und die Art der Beziehungen zwischen ihnen allen. Es ist eine Frage des erneuten Überdenkens des Entwicklungspfades, der andere Logik, Visionen, Interessen und Strategien aller Beteiligten, unserer so genannten Akteure einschließt. Ob dies von endogenen Initiativen oder neuen gemeinsamen Projekten ausgeht: man wird in einen Prozess kollektiven Lernens eintreten, den Paul Singer und Clarita Müller-Plantenberg erläutern und entwickeln in dem Konzept der Inkubation und Solidarischen Ökonomie, die Eigeninitiative, Selbstbestimmung und Selbstverwaltung von lokalen Gemeinschaften und die Öffnung für eine Neu-Konzeptualisierung und Institutionalisierung einschließt. So ein Prozess ist nur mit einem interdisziplinären Rahmen möglich. Dieser Rahmen soll auf einer zusätzlicher Kommunikation zwischen den Akteuren und Sozialwissenschaften beruhen und mit jenen, die auf dem Feld der Technologie arbeiten. So können dann technische „Experten“ angesichts eines technischen Projektfehlers, der aufgrund von bestimmten sozialen und kulturellen Realitäten zustande kam sagen, „es ist kein Scheitern ; es war ein Schritt innerhalb eines Lernprozesse der in die technischen Projekte und Studien einbezogen werden muss“. Wir haben das Energiethema gewählt; und insbesondere, Energie für eine nachhaltige ländliche Entwicklung in Subsahara-Afrika, um den Weg von der Theorie in die Praxis zu illustrieren und experimentell auszuprobieren, den Weg von den Beobachtungen zu der Veränderung, wobei Fragen, Annahmen, Strategien und konkrete Aktionen für den Wandel behandelt werden. Wir nennen unseren experimentellen Weg: DRIEE, das heißt auf Deutsch Ländliche Entwicklung und Inkubation von Energieunternehmen. Dabei gehen wir davon aus, dass: - Energie im Allgemeinen auf der internationalen Ebene fast gleichbedeutend mit Elektrizität ist. Heute bestehen die wichtigsten Bedürfnisse nach Energie dort wo die agro-pastorale Produktion, das Kochen, die Nahrungsmittelkonservierung und Verarbeitung …etc. stattfindet. - Diese ländliche Bevölkerung zu etwa 80% der nationalen Wirtschaft ausmacht. Dass sie gleichzeitig aber nur zu weniger als 5% der Energieproduktion Zugang hat, was oft auf Licht reduziert ist und nicht einmal ihrer Produktion zugute kommen kann. - Die Projekte für Energie und Elektrizität vor allem auf die Technologischen Fragen konzentriert sind und weniger auf die Bedürfnisse. Fast die Gesamtheit der Fonds für Energie wird in Bezug auf die Investitionen Infrastruktur der Produktion und Verteilung durch die konventionellen zentralisierten Netze geplant. Angesichts dieser Analysen gehen die in dieser Arbeit vorgenommenen Studien in Gambia und Kamerun von Bestandsaufnahmen und / oder beschreibenden regionalen Analysen aus: - von Bedürfnissen, von Praktiken und lokalen Initiativen von Fragen der Energie, für einzelne Professionen, Haushalte, Gruppen, spezifische Gruppen, wie Frauen, ländliche Gemeinden mit ihren spezifischen Charakteristika. - Von Potentialen: natürliche lokale Energieressourcen, soziokulturelle Ressourcen – so z.B. die empirisch feststellbaren menschliche Ressourcen wie endogenes Wissen und praktische organisatorische Fähigkeiten gegenüber den Problemen der Energie. Dieser experimentelle Schritt von Handlungsforschung (DRIEE) in Kamerun führte zu der Gründung einer Organisation, über die und mit der wir die Logik der Inkubation und Solidarischen Ökonomie einführen. Das ist FERDEDSI, das heißt auf Deutsch „Forum für Erneuerbare Energie – Nachhaltige Entwicklung und Internationale Solidarität“. Zunächst war dies eine Energiegenossenschaft und dann (im Prozess) wurde es zu einer institutionellen Nische von mehreren Mikro Initiativen in ländlichen Gebieten. FERDEDSI ist ein Prozess der Inkubation und ein Inkubator ist also gleichzeitig ein inkubiertes Energieunternehmen aber auch ein Inkubator für lokale Organisationen. Die ersten Aktionen finden in den Departments von Noun und Ménoua in der westlichen Provinz von Kamerun statt. Während der Forschungsperiode findet akademische Austausch statt (Nord-Süd und Süd-Süd), diese ist dabei zu formalen Partnerschaften zu werden, nicht nur zwischen Universitäten sondern genauer lokale Organisationen und Universitäten. Dieser letzte Typ von Partnerschaften, die die solidarische Ökonomie ausmachen ist auch eine Innovation des Prozesses für die afrikanischen Fälle, die dem Beispiel dessen, was in Lateinamerika geschieht, folgen. So kommt es zu gegenseitiger sinnvoller Ausbildung in den internationalen Arbeitsgruppen und Seminaren der Universität.

Optimization-Based Robotic Manipulation for Safe Interaction with Human Operators

This thesis investigates a method for human-robot interaction (HRI) in order to uphold productivity of industrial robots like minimization of the shortest operation time, while ensuring human safety like collision avoidance. For solving such problems an online motion planning approach for robotic manipulators with HRI has been proposed. The approach is based on model predictive control (MPC) with embedded mixed integer programming. The planning strategies of the robotic manipulators mainly considered in the thesis are directly performed in the workspace for easy obstacle representation. The non-convex optimization problem is approximated by a mixed-integer program (MIP). It is further effectively reformulated such that the number of binary variables and the number of feasible integer solutions are drastically decreased. Safety-relevant regions, which are potentially occupied by the human operators, can be generated online by a proposed method based on hidden Markov models. In contrast to previous approaches, which derive predictions based on probability density functions in the form of single points, such as most likely or expected human positions, the proposed method computes safety-relevant subsets of the workspace as a region which is possibly occupied by the human at future instances of time. The method is further enhanced by combining reachability analysis to increase the prediction accuracy. These safety-relevant regions can subsequently serve as safety constraints when the motion is planned by optimization. This way one arrives at motion plans that are safe, i.e. plans that avoid collision with a probability not less than a predefined threshold. The developed methods have been successfully applied to a developed demonstrator, where an industrial robot works in the same space as a human operator. The task of the industrial robot is to drive its end-effector according to a nominal sequence of grippingmotion-releasing operations while no collision with a human arm occurs.

Institutions, Behavior and Evolution

The three articles constituting this thesis are for reasons of content or method related to the following three fields in economics: Behavioral Economics, Evolutionary Game Theory and Formal Institutional Economics. A core element of these fields is the concept of individual preferences. Preferences are of central importance for the conceptional framework to analyze human behavior. They form the foundation for the theory of rational choice which is defined by the determination of the choice set and the selection of the most preferred alternative according to some consistency requirements. The theory of rational choice is based on a very simplified description of the problem of choice (object function and constraints). However, that choices depend on many more factors is for instance propagated by psychological theories and is supported by many empirical and experimental studies. This thesis adds to a better understanding of individual behavior to the extent that the evolution of certain characteristics of preferences and their consequences on human behavior forms the overarching theme of the dissertation. The long-term effect of evolutionary forces on a particular characteristic of importance in the theoretical, empirical and experimental economic literature, the concept of inequality aversion, is subject of the article “The evolution of inequality aversion in a simplified game of life” (Chapter 4). The contribution of the article is the overcoming of a restriction of former approaches to analyze the evolution of preferences in very simple environments. By classifying human interaction into three central economic games, the article provides a first step towards a simplified and sufficiently complete description of the interaction environment. Within such an environment the article characterizes the evolutionary stable preference distribution. One result shows, that the interaction of the aforementioned three classes can stabilize a preference of inequality aversion in the subpopulation which is favored in the problem of redistribution. The two remaining articles are concerned with social norms, which dissemination is determined by medium-run forces of cultural evolution. The article “The impact of market innovations on the evolution of social norms: the sustainability case.“ (Chapter 2) studies the interrelation between product innovations which are relevant from a sustainability perspective and an according social norm in consumption. This relation is based on a conformity bias in consumption and the attempt to avoid cognitive dissonances resulting from non-compliant consumption. Among others, it is shown that a conformity bias on the consumption side can lead to multiple equilibria on the side of norm adoption. The article “Evolution of cooperation in social dilemmas: signaling internalized norms.” (Chapter 3) studies the emergence of cooperation in social dilemmas based on the signaling of social norms. The article provides a potential explanation of cooperative behavior, which does not rely on the assumption of structured populations or on the unmotivated ability of social norms to restrict individual actions or strategy spaces. A comprehensive result of the single articles is the explanation of the phenomenon of partial norm adaption or dissemination of preferences. The plurality of the applied approaches with respect to the proximity to the rational choice approach and regarding the underlying evolutionary mechanics is a particular strength of the thesis. It shows the equality of these approaches in their potential to explain the phenomenon of cooperation in environments that provide material incentives for defective behavior. This also points to the need of a unified framework considering the biological and cultural coevolution of preference patterns.

Hierarchical Object Recognition Using Libraries of Parameterized Model Sub-Parts

This thesis describes the development of a model-based vision system that exploits hierarchies of both object structure and object scale. The focus of the research is to use these hierarchies to achieve robust recognition based on effective organization and indexing schemes for model libraries. The goal of the system is to recognize parameterized instances of non-rigid model objects contained in a large knowledge base despite the presence of noise and occlusion. Robustness is achieved by developing a system that can recognize viewed objects that are scaled or mirror-image instances of the known models or that contain components sub-parts with different relative scaling, rotation, or translation than in models. The approach taken in this thesis is to develop an object shape representation that incorporates a component sub-part hierarchy- to allow for efficient and correct indexing into an automatically generated model library as well as for relative parameterization among sub-parts, and a scale hierarchy- to allow for a general to specific recognition procedure. After analysis of the issues and inherent tradeoffs in the recognition process, a system is implemented using a representation based on significant contour curvature changes and a recognition engine based on geometric constraints of feature properties. Examples of the system's performance are given, followed by an analysis of the results. In conclusion, the system's benefits and limitations are presented.

Enhancing the Dexterity of a Robot Hand Using Controlled Slip

Humans can effortlessly manipulate objects in their hands, dexterously sliding and twisting them within their grasp. Robots, however, have none of these capabilities, they simply grasp objects rigidly in their end effectors. To investigate this common form of human manipulation, an analysis of controlled slipping of a grasped object within a robot hand was performed. The Salisbury robot hand demonstrated many of these controlled slipping techniques, illustrating many results of this analysis. First, the possible slipping motions were found as a function of the location, orientation, and types of contact between the hand and object. Second, for a given grasp, the contact types were determined as a function of the grasping force and the external forces on the object. Finally, by changing the grasping force, the robot modified the constraints on the object and affect controlled slipping slipping motions.

Natural Object Categorization

This thesis addresses the problem of categorizing natural objects. To provide a criteria for categorization we propose that the purpose of a categorization is to support the inference of unobserved properties of objects from the observed properties. Because no such set of categories can be constructed in an arbitrary world, we present the Principle of Natural Modes as a claim about the structure of the world. We first define an evaluation function that measures how well a set of categories supports the inference goals of the observer. Entropy measures for property uncertainty and category uncertainty are combined through a free parameter that reflects the goals of the observer. Natural categorizations are shown to be those that are stable with respect to this free parameter. The evaluation function is tested in the domain of leaves and is found to be sensitive to the structure of the natural categories corresponding to the different species. We next develop a categorization paradigm that utilizes the categorization evaluation function in recovering natural categories. A statistical hypothesis generation algorithm is presented that is shown to be an effective categorization procedure. Examples drawn from several natural domains are presented, including data known to be a difficult test case for numerical categorization techniques. We next extend the categorization paradigm such that multiple levels of natural categories are recovered; by means of recursively invoking the categorization procedure both the genera and species are recovered in a population of anaerobic bacteria. Finally, a method is presented for evaluating the utility of features in recovering natural categories. This method also provides a mechanism for determining which features are constrained by the different processes present in a multiple modal world.

The Use of Grouping in Visual Object Recognition.

The report describes a recognition system called GROPER, which performs grouping by using distance and relative orientation constraints that estimate the likelihood of different edges in an image coming from the same object. The thesis presents both a theoretical analysis of the grouping problem and a practical implementation of a grouping system. GROPER also uses an indexing module to allow it to make use of knowledge of different objects, any of which might appear in an image. We test GROPER by comparing it to a similar recognition system that does not use grouping.

Generating Compliant Motion of Objects with an Articulated Hand

The flexibility of the robot is the key to its success as a viable aid to production. Flexibility of a robot can be explained in two directions. The first is to increase the physical generality of the robot such that it can be easily reconfigured to handle a wide variety of tasks. The second direction is to increase the ability of the robot to interact with its environment such that tasks can still be successfully completed in the presence of uncertainties. The use of articulated hands are capable of adapting to a wide variety of grasp shapes, hence reducing the need for special tooling. The availability of low mass, high bandwidth points close to the manipulated object also offers significant improvements I the control of fine motions. This thesis provides a framework for using articulated hands to perform local manipulation of objects. N particular, it addresses the issues in effecting compliant motions of objects in Cartesian space. The Stanford/JPL hand is used as an example to illustrate a number of concepts. The examples provide a unified methodology for controlling articulated hands grasping with point contacts. We also present a high-level hand programming system based on the methodologies developed in this thesis. Compliant motion of grasped objects and dexterous manipulations can be easily described in the LISP-based hand programming language.

Concurrent Aggregates (CA): An Object-Oriented Language for Fine-Grained Message-Passing Machines

Fine-grained parallel machines have the potential for very high speed computation. To program massively-concurrent MIMD machines, programmers need tools for managing complexity. These tools should not restrict program concurrency. Concurrent Aggregates (CA) provides multiple-access data abstraction tools, Aggregates, which can be used to implement abstractions with virtually unlimited potential for concurrency. Such tools allow programmers to modularize programs without reducing concurrency. I describe the design, motivation, implementation and evaluation of Concurrent Aggregates. CA has been used to construct a number of application programs. Multi-access data abstractions are found to be useful in constructing highly concurrent programs.

Statistical Object Recognition

Two formulations of model-based object recognition are described. MAP Model Matching evaluates joint hypotheses of match and pose, while Posterior Marginal Pose Estimation evaluates the pose only. Local search in pose space is carried out with the Expectation--Maximization (EM) algorithm. Recognition experiments are described where the EM algorithm is used to refine and evaluate pose hypotheses in 2D and 3D. Initial hypotheses for the 2D experiments were generated by a simple indexing method: Angle Pair Indexing. The Linear Combination of Views method of Ullman and Basri is employed as the projection model in the 3D experiments.

Attentional Selection in Object Recognition

A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.

An Analysis of the Effect of Gaussian Error in Object Recognition

Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

Contact Sensing: A Sequential Decision Approach to Sensing Manipulation Contact

This paper describes a new statistical, model-based approach to building a contact state observer. The observer uses measurements of the contact force and position, and prior information about the task encoded in a graph, to determine the current location of the robot in the task configuration space. Each node represents what the measurements will look like in a small region of configuration space by storing a predictive, statistical, measurement model. This approach assumes that the measurements are statistically block independent conditioned on knowledge of the model, which is a fairly good model of the actual process. Arcs in the graph represent possible transitions between models. Beam Viterbi search is used to match measurement history against possible paths through the model graph in order to estimate the most likely path for the robot. The resulting approach provides a new decision process that can be use as an observer for event driven manipulation programming. The decision procedure is significantly more robust than simple threshold decisions because the measurement history is used to make decisions. The approach can be used to enhance the capabilities of autonomous assembly machines and in quality control applications.