7 research outputs found

    Behavioural Adaptation towards Efficient Resource Sharing under the Lack of Communication

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    This paper introduces a novel multi-agent model for simulating water sharing scenarios under various irrigation policies, together with a novel self adaptive learning algorithm that achieves efficient resource allocation. The main contribution of this work lies in the fact that both the multi-agent model and the proposed learning algorithm operate under the lack of communication between the users of the resource, thus, no assumptions about the development of relations of trust between them are made. Moreover, the proposed learning algorithm uses only local information and operates in a decentralized manner, thus its implementation does not entail significant costs. The model was calibrated using data from a real world ecosystem and experimental results provided statistical and qualitative figures of merit for assessing typical irrigation policies. For all the irrigation policies examined, even if the users of the resource acted under profit maximization criteria, the proposed learning algorithm provided a means of achieving efficient resource allocation, despite the lack of communication. Thus, the proposed model and learning algorithm are valuable tools for assessing alternative irrigation policies and providing the best policy for any given scenario

    Design requirements of a virtual learning environment for resource sharing

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    This study presents the evaluation of the design requirements of a novel model-supported virtual environment appropriate for environmental education, where the simulation process is controlled by a novel multi-agent model. The virtual environment was qualitatively evaluated by 14 students, that provided feedback about the accuracy of the graphical representations, the usability and interaction of the interface and the comprehension of the underlying process. Students suggestions were taken under consideration, modifying the virtual environment to its final form. © 2012 Springer-Verlag

    A model supported interactive virtual environment for natural resource sharing in environmental education

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    This paper introduces a realistic 3D model supported virtual environment for environmental education, that highlights the importance of water resource sharing by focusing on the tragedy of the commons dilemma. The proposed virtual environment entails simulations that are controlled by a multi-agent simulation model of a real ecosystem consisting of a lake that is being drained by a community of farmers with different types of behaviours. This resembles real-life scenarios, where farmers operate under extreme economic pressure. The virtual environment provides realistic visualization of the elements of the multi-agent model in a comprehensible manner, while keeping the details and the complexity of the ecosystem hidden from the students. Extensive experiments were conducted using students divided in a control group, exposed to conventional teaching means, and an experimental group that used the proposed virtual environment. Both groups were administered questionnaires at pre-test and post-test intervals, and conclusions were drawn after qualitative and quantitative analysis of the results. It was revealed that the proposed virtual environment provided significant cognitive advancements for the students, especially for complex inter-related notions, thus constituting a valuable tool for environment education. (C) 2012 Elsevier Ltd. All rights reserved

    Investigating the effect of meta-cognitive scaffolding for learning by teaching

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    This paper investigates the effect of meta-cognitive help in the context of learning by teaching. Students learned to solve algebraic equations by tutoring a teachable agent, called SimStudent, using an online learning environment, called APLUS. A version of APLUS was developed to provide meta-cognitive help on what problems students should teach, as well as when to quiz SimStudent. A classroom study comparing APLUS with and without the meta-cognitive help was conducted with 173 seventh to ninth grade students. The data showed that students with the meta-cognitive help showed better problem selection and scored higher on the post-test than those who tutored SimStudent without the meta-cognitive help. These results suggest that, when carefully designed, learning by teaching can support students to not only learn cognitive skills but also employ meta-cognitive skills for effective tutoring. © 2014 Springer International Publishing Switzerland

    A constrained multi-agent system compensating for self-lucrative behaviours in water resource sharing

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    This paper presents the development of a multi-agent model for simulating realistic water-sharing scenarios and a means of studying and assessing an ecosystem's viability by taking under consideration environmental and socio-economical parameters. To account for farmer self-lucrative behaviours, exhibited due to the economic pressure exerted on them, the proposed model imposes constraints such as the lack of inter-farmer communication and observation. Additionally, a self-adaptive learning algorithm is proposed that compensates for such self-lucrative behaviours, despite the imposed constraints. The proposed model was calibrated using data derived from the Lake Koronia ecosystem, and experimental results provided statistical and objective figures of merit for assessing typical irrigation policies under study. As it will be demonstrated, the developed model is a viable means for assessing irrigation policies, and the proposed self-adaptive learning method is a means of guiding behaviours towards the viability of both the resource and its users

    Learning activities as enactments of learning affordances in MUVEs: A review-based classification

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