14,761 research outputs found

    Incentive-compatible mechanisms for norm monitoring in open multi-agent systems (Extended abstract)

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    We consider the problem of detecting norm violations in open multi-agent systems (MAS). In this extended abstract, we outline the approach of [Alechina et al., 2018], and show how, using ideas from scrip systems, we can design mechanisms where the agents comprising the MAS are incen-tivised to monitor the actions of other agents for norm violation

    Integrating driving forces into the development of Adaptive Virtual Organizations

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    Organizations have become the backbone of the society. Humans live around all kinds of organizations, such as neighborhood communities, businesses, schools, unions, political, sports, and religious organizations, etc. These organizations have a set of members, each playing a specific role, which determines their duties and functionalities within the organization. One of these functionalities is to offer a range of services to members of the organization and external people. These members must follow a set of norms to ensure the proper functioning of the organization and should pursue the global goals of the organization. A feature that is repeated in organizations is that they are not static but dynamic, resulting in changes in both its structure and the way in which they behave. In an organization, any of its elements is prone to change due to situations that occur in the organization itself or its environment. Researchers in the field of social sciences and organizations have studied such situations, the reasons why they appear and solutions and actions to be taken to ensure that this situation does not damage the organization or to take advantage of the situation. These situations are known as ‘Forces that drive organizational change’. Human organizations are the main source of inspiration for the Multi-Agent Systems (MAS) based on organizations. These systems are computational abstractions that are populated by agents instead of people, but take into account organizational elements such as roles, services, goals, norms, etc. However, the proposals that have been presented up to now to define this type of MAS are focused mostly on static systems, without changes in its structure. Moreover, in the few proposals that take into account organizational changes, they just state that changes occur, but without specifying the reason for change. Thus, the concept of ‘forces that drive organizational change’ (and their features) is not considered. Therefore, the objective of this PhD thesis is to translate the knowledge of the forces that drive organizational change available in human organizations to MASbased organizations. These forces will be formally expressed with the factors that help to detect them. The solutions to be taken when a force is detected will also be presented. To correctly perform this task, a formalization for virtual organizations is designed, named Virtual Organization Formalization (VOF). Moreover, the Artifacts for Organizational Mechanisms are proposed, which are a tool to help in the representation of organizational knowledge and in the modeling of the environment of the organization. This tool is based on the Agents & Artifacts (A&A) framework.Esparcia García, S. (2015). Integrating driving forces into the development of Adaptive Virtual Organizations [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/48538TESI

    Multi-attribute auctions with different types of attributes: Enacting properties in multi-attribute auctions

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    International audienceMulti-attribute auctions allow agents to sell and purchase goods and services taking into account more attributes besides the price (e.g. service time, tolerances, qualities, etc.). In this paper we analyze attributes involved during the auction process and propose to classify them between verifiable attributes, unverifiable attributes and auctioneer provided attributes. According to this classification we present VMA2, a new Vickrey-based reverse multi-attribute auction mechanism which, taking into account the different types of attributes involved in the auction, allows the auction customization in order to suit the auctioneer needs. On the one hand, the use of auctioneer provided attributes enables the inclusion of different auction concepts such as social welfare, trust or robustness whilst, on the other hand, the use of verifiable attributes guarantee truthful bidding. The paper exemplifies the behaviour of VMA2 describing how an egalitarian allocation can be achieved. The mechanism is then tested in a simulated manufacturing environment and compared with other existing auction allocation methods

    Modeling Cognitive Social Capital and Corporate Social Responsibility (CSR) as Preconditions for Sustainable Networks of Relations

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    The paper studies the relationship between social capital (SC) and Corporate Social Responsibility (CSR) by investigating the idea of a virtuous circle between the level of SC and the implementation of CSR practices that favours the creation of cooperative networks between the firm and all its stakeholders by promoting the spread of social norms of trust, trustworthiness and cooperation. Following the literature on SC that stresses its multidimensional character (e.g. Paldam 2000), we consider two dimensions of this notion. Starting from the distinction introduced by Uphoff (1999), we take into account a cognitive and a structural idea of SC. The first one essentially refers to the dispositional characters of agents that affect their propensity to behave in different ways. The latter refers to social networks connecting agents.With regard to the concept of CSR, we adopt a contractarian approach and consider CSR as an extended model of corporate governance, based on the fiduciary duties owed to all the firm's stakeholders. Among stakeholders, we distinguish between strong and weak stakeholders. Both these two categories have made specific investments in the firm. However, strong stakeholders are precious for the firm because they bring in strategic assets. They are, for example, skilled workers or institutional investors. On the contrary, weak stakeholders do not bring strategic assets into the firm and firms have material incentives at defecting in the relationship with them. They are, for example, unskilled workers. By using the tools of psychological game theory, the paper shows the role of cognitive social capital and the adoption of CSR practices in promoting the emergence of social norms of trust, trustworthiness and cooperation which favour the creation of cooperative networks between the firm and all its stakeholders (structural social capital). In particular, we show that: a) the level of cognitive SC plays a key role in inducing the firm to adopt and observe CSR practices that respect all the stakeholders; b) the decision of adopting formal instruments of CSR contributes to create cognitive SC that is endogenously determined in the model; c) the level of cognitive SC and the decision of adopting CSR practices creates structural SC in terms of a long term relationship between the firm and the weak and strong stakeholders.

    The future of securitization

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    Securitization is a financial innovation that experiences a boom-bust cycle, as many other innovations before. This paper analyzes possible reasons for the breakdown of primary and secondary securitization markets, and argues that misaligned incentives along the value chain are the primary cause of the problems. The illiquidity of asset and interbank markets, in this view, is a market failure derived from ill-designed mechanisms of coordinating financial intermediaries and investors. Thus, illiquidity is closely related to the design of the financial chains. Our policy conclusions emphasize crisis prevention rather than crisis management, and the objective is to restore a “comprehensive incentive alignment”. The toe-hold for strengthening regulation is surprisingly small. First, we emphasize the importance of equity piece retention for the long-term quality of the underlying asset pool. As a consequence, equity piece allocation needs to be publicly known, alleviating market pricing. Second, on a micro level, accountability of managers can be improved by compensation packages aiming at long term incentives, and penalizing policies with destabilizing effects on financial markets. Third, on a macro level, increased transparency relating to effective risk transfer, risk-related management compensation, and credible measurement of rating performance stabilizes the valuation of financial assets and, hence, improves the solvency of financial intermediaries. Fourth, financial intermediaries, whose risk is opaque, may be subjected to higher capital requirements

    A Mechanism Design Approach to Bandwidth Allocation in Tactical Data Networks

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    The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems\u27. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today\u27s software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest to the defense community. In this thesis, we consider a scenario where a number of military platforms have been tasked with the goal of detecting and tracking targets. The sensors onboard a military platform have a partial and inaccurate view of the operating picture and need to make use of data transmitted from neighboring sensors in order to improve the accuracy of their own measurements. The communication takes place over tactical data networks with scarce bandwidth. The problem is compounded by the possibility that the local goals of military platforms might not be aligned with the global system goal. Such a scenario might occur in multi-flag, multi-platform military exercises, where the military commanders of each platform are more concerned with the well-being of their own platform over others. Therefore there is a need to design a mechanism that efficiently allocates the flow of data within the network to ensure that the resulting global performance maximizes the information gain of the entire system, despite the self-interested actions of the individual actors. We propose a two-stage mechanism based on modified strictly-proper scoring rules, with unknown costs, whereby multiple sensor platforms can provide estimates of limited precisions and the center does not have to rely on knowledge of the actual outcome when calculating payments. In particular, our work emphasizes the importance of applying robust optimization techniques to deal with the uncertainty in the operating environment. We apply our robust optimization - based scoring rules algorithm to an agent-based model framework of the combat tactical data network, and analyze the results obtained. Through the work we hope to demonstrate how mechanism design, perched at the intersection of game theory and microeconomics, is aptly suited to address one set of challenges of the ULS system paradigm - challenges not amenable to traditional system engineering approaches

    Market fields structure & dynamics in industrial automation

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    There is a research tradition in the economics of standards which addresses standards wars, antitrust concerns or positive externalities from standards. Recent research has also dealt with the process characteristics of standardisation, de facto standard-setting consortia and intellectual property concerns in the technology specification or implementation phase. Nonetheless, there are no studies which analyse capabilities, comparative industry dynamics or incentive structures sufficiently in the context of standard-setting. In my study, I address the characteristics of collaborative research and standard-setting as a new mode of deploying assets beyond motivations well-known from R&D consortia or market alliances. On the basis of a case study of a leading user organisation in the market for industrial automation technology, but also a descriptive network analysis of cross-community affiliations, I demonstrate that there must be a paradoxical relationship between cooperation and competition. More precisely, I explain how there can be a dual relationship between value creation and value capture respecting exploration and exploitation. My case study emphasises the dynamics between knowledge stocks (knowledge alignment, narrowing and deepening) produced by collaborative standard setting and innovation; it also sheds light on an evolutional relationship between the exploration of assets and use cases and each firm's exploitation activities in the market. I derive standard-setting capabilities from an empirical analysis of membership structures, policies and incumbent firm characteristics in selected, but leading, user organisations. The results are as follows: the market for industrial automation technology is characterised by collaboration on standards, high technology influences of other industries and network effects on standards. Further, system integrators play a decisive role in value creation in the customer-specific business case. Standard-setting activities appear to be loosely coupled to the products offered on the market. Core leaders in world standards in industrial automation own a variety of assets and they are affiliated to many standard-setting communities rather than exclusively committed to a few standards. Furthermore, their R&D ratios outperform those of peripheral members and experience in standard-setting processes can be assumed. Standard-setting communities specify common core concepts as the basis for the development of each member's proprietary products, complementary technologies and industrial services. From a knowledge-based perspective, the targeted disclosure of certain knowledge can be used to achieve high innovation returns through systemic products which add proprietary features to open standards. Finally, the interplay between exploitation and exploration respecting the deployment of standard-setting capabilities linked to cooperative, pre-competitive processes leads to an evolution in common technology owned and exploited by the standard-setting community as a particular kind of innovation ecosystem. --standard-setting,innovation,industry dynamics and context,industrial automation

    Civil Society Legitimacy and Accountability: Issues and Challenges

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    University education rarely focuses its attention and imagination on teaching students how to turn a vision into reality; how to design, develop, and lead social change organizations. The author co-created the Social Entrepreneurship Collaboratory (SE Lab) at Stanford University and then Harvard University as a model educational program designed to achieve this goal. The SE Lab is a Silicon Valley influenced incubator where student teams create and develop innovative pilot projects for US and international social sector initiatives. The lab combines academic theory, frameworks, and traditional research with intensive field work, action research, peer support and learning, and participation of domain experts and social entrepreneurship practitioners. It also provides students an opportunity to collaborate on teams to develop business plans for their initiatives and to compete for awards and recognition in the marketplace of ideas. Students in the SE Lab have created innovative organizations serving many different social causes, including fighting AIDS in Africa, promoting literacy in Mexico, combating the conditions for terrorism using micro-finance in the Palestinian territories, and confronting gender inequality using social venture capital to empower women in Afghanistan
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