State of the art review of the existing soft computing based approaches to trust and reputation computation

In this paper we present a state of the art review of PageRanktrade based approaches for trust and reputation computation. We divide the approaches that make use of PageRanktrade method for trust and reputation computation, into six different classes. Each of the six classes is discussed in this paper

Economic incentive patterns and their application to ad hoc networks

While research about cooperation incentives for mobile ad hoc networks (MANETs) is done only for a relative short period, there exists tremendous knowledge in the economic and social areas. Based on a new categorization of incentive patterns, we examine the relevant properties of each pattern and demonstrate their respective design alternatives and occurring challenges for the application to ad hoc networks. With a focus on trade based patterns, we found that negotiation about actions proves to be very complex or inefficient in MANETs. Another approach, the introduction of an artificial currency, also implies several problems like how to equip the entities with means of payment and how to secure liquidity. As a novelty, we introduce a new kind of incentive pattern following the concept of company shares. It suits well for MANETs because it can be shown that through the creation of individual currencies the above mentioned problems disappear

Encouraging contributions in Learning Networks using incentive mechanisms

Please refer to the original Article: Hummel, H., Burgos, D., Tattersall, C., Brouns, F., Kurvers, H., Koper, R. (2005). Encouraging constributions in learning networks using incentive mechanisms. Journal of Computer Assisted Learning,21, 355-365. Submitted (April 8,2005)We investigate incentive mechanisms to increase active participation in Learning Networks. The Learning Network under study is LN4LD, a Learning Network for the exchange of information about the IMS Learning Design specification. We examine how to encourage learners in LN4LD to contribute their knowledge, and whether incentive mechanisms can increase the level of active participation. We describe an incentive mechanism based on constructivist principles and Social Exchange Theory, and experimentation using the mechanism designed to increase the level of active participation. The incentive mechanism allows individual learners to gain personal access to additional information through the accumulation of points earned by making contributions. Repeated measurements according to a simple interrupted time series with removal design show that the level of participation was indeed increased by the introduction of the reward system. It can therefore be considered worthwhile to use incentive mechanisms in Learning Networks

On the convergence of autonomous agent communities

This is the post-print version of the final published paper that is available from the link below. Copyright @ 2010 IOS Press and the authors.Community is a common phenomenon in natural ecosystems, human societies as well as artificial multi-agent systems such as those in web and Internet based applications. In many self-organizing systems, communities are formed evolutionarily in a decentralized way through agents' autonomous behavior. This paper systematically investigates the properties of a variety of the self-organizing agent community systems by a formal qualitative approach and a quantitative experimental approach. The qualitative formal study by applying formal specification in SLABS and Scenario Calculus has proven that mature and optimal communities always form and become stable when agents behave based on the collective knowledge of the communities, whereas community formation does not always reach maturity and optimality if agents behave solely based on individual knowledge, and the communities are not always stable even if such a formation is achieved. The quantitative experimental study by simulation has shown that the convergence time of agent communities depends on several parameters of the system in certain complicated patterns, including the number of agents, the number of community organizers, the number of knowledge categories, and the size of the knowledge in each category

MACE – Enriching Architectural Learning Objects for Experience Multiplication.

Stefaner, M., Dalla Vecchia, E., Condotta, M., Wolpers, M., Specht, M., Apelt, M., Duval, E. (2007) MACE – Enriching Architectural Learning Objects for Experience Multiplication. In: Duval, E., Klamma, R., & Wolpers, M. (eds.) EC-TEL 2007. LNCS 4753; Berlin, Heidelberg: Springer; pp. 322-336.Education in architecture requires access to a broad range of architectural learning material to develop flexibility and creativity in design. The learning material is compromised of digital information captured in textual and visual media including single images, videos, description of architectural concepts or complete architectural projects, i.e. digital artifacts on different aggregation levels. The repositories storing such information are not interrelated and do not provide unified access so that retrieval of architectural learning objects is cumbersome and time consuming. In this paper, we describe how an infrastructure of federated architectural learning repositories will provide unique, integrated access facilities for high quality architectural content. The integration of various types of content, usage, social and contextual metadata enables users to develop multiple perspectives and navigation paths that support experience multiplication for the user. A service– oriented software architecture that is based on open standards, and a flexible user interface design solutions based on widgets ensure easy integration and re- combinability of contents, metadata and functionalities

Engineering incentive schemes for ad hoc networks: a case study for the lanes overlay [online]

In ad hoc networks, devices have to cooperate in order to compensate for the absence of infrastructure. Yet, autonomous devices tend to abstain from cooperation in order to save their own resources. Incentive schemes have been proposed as a means of fostering cooperation under these circumstances. In order to work effectively, incentive schemes need to be carefully tailored to the characteristics of the cooperation protocol they should support. This is a complex and demanding task. However, up to now, engineers are given virtually no help in designing an incentive scheme. Even worse, there exists no systematic investigation into which characteristics should be taken into account and what they imply. Therefore, in this paper, we propose a systematic approach for the engineering of incentive schemes. The suggested procedure comprises the analysis and adjustment of the cooperation protocol, the choice of appropriate incentives for cooperation, and guidelines for the evaluation of the incentive scheme. Finally, we show how the proposed procedure is successfully applied to a service discovery overlay