7,518 research outputs found

    Efficient Order and Resource Coordination in Mass Customization

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    Mass customization manufacturing systems require a high level of adaptability and flexibility in production – especially in production planning and control. In particular, the Coordination of orders and resources is critical, because of the high volatility and the make to order principle. Multi-agent systems theoretically provide the required features to handle that complexity, but a lack of informational integration and organizational incompatibilities lead to low applicability. The application of Internet Technology provides the necessary interoperability and organizational alignment to support an overall application of multi-agent systems in mass customization.Mass Customization; Internet Technologies; Multi Agent Systems; Production Planning and Control

    Proceedings of the 11th European Agent Systems Summer School Student Session

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    This volume contains the papers presented at the Student Session of the 11th European Agent Systems Summer School (EASSS) held on 2nd of September 2009 at Educatorio della Providenza, Turin, Italy. The Student Session, organised by students, is designed to encourage student interaction and feedback from the tutors. By providing the students with a conference-like setup, both in the presentation and in the review process, students have the opportunity to prepare their own submission, go through the selection process and present their work to each other and their interests to their fellow students as well as internationally leading experts in the agent field, both from the theoretical and the practical sector. Table of Contents: Andrew Koster, Jordi Sabater Mir and Marco Schorlemmer, Towards an inductive algorithm for learning trust alignment . . . 5; Angel Rolando Medellin, Katie Atkinson and Peter McBurney, A Preliminary Proposal for Model Checking Command Dialogues. . . 12; Declan Mungovan, Enda Howley and Jim Duggan, Norm Convergence in Populations of Dynamically Interacting Agents . . . 19; Akın Günay, Argumentation on Bayesian Networks for Distributed Decision Making . . 25; Michael Burkhardt, Marco Luetzenberger and Nils Masuch, Towards Toolipse 2: Tool Support for the JIAC V Agent Framework . . . 30; Joseph El Gemayel, The Tenacity of Social Actors . . . 33; Cristian Gratie, The Impact of Routing on Traffic Congestion . . . 36; Andrei-Horia Mogos and Monica Cristina Voinescu, A Rule-Based Psychologist Agent for Improving the Performances of a Sportsman . . . 39; --Autonomer Agent,Agent,Künstliche Intelligenz

    Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO

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    We present the results of the second Neural MMO challenge, hosted at IJCAI 2022, which received 1600+ submissions. This competition targets robustness and generalization in multi-agent systems: participants train teams of agents to complete a multi-task objective against opponents not seen during training. We summarize the competition design and results and suggest that, considering our work as a case study, competitions are an effective approach to solving hard problems and establishing a solid benchmark for algorithms. We will open-source our benchmark including the environment wrapper, baselines, a visualization tool, and selected policies for further research.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Interactive Intelligenc

    Enhancing Peer-to-Peer Applications with Multi-agent Systems

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    This paper copes with the problem of integrating peer-to-peer and multi-agent systems for the realization of both large-scale multi-agent systems and sophisticated peer-to-peer applications. In particular, it presents how JADE, one of the best known and most used software framework for the development of multi-agent systems, has been extended with a peer-to-peer technology, and how a JADE multi-agent system can be overlapped over a peer-to-peer system to provide more sophisticated services

    Application of lean scheduling and production control in non-repetitive manufacturing systems using intelligent agent decision support

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    This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Lean Manufacturing (LM) is widely accepted as a world-class manufacturing paradigm, its currency and superiority are manifested in numerous recent success stories. Most lean tools including Just-in-Time (JIT) were designed for repetitive serial production systems. This resulted in a substantial stream of research which dismissed a priori the suitability of LM for non-repetitive non-serial job-shops. The extension of LM into non-repetitive production systems is opposed on the basis of the sheer complexity of applying JIT pull production control in non-repetitive systems fabricating a high variety of products. However, the application of LM in job-shops is not unexplored. Studies proposing the extension of leanness into non-repetitive production systems have promoted the modification of pull control mechanisms or reconfiguration of job-shops into cellular manufacturing systems. This thesis sought to address the shortcomings of the aforementioned approaches. The contribution of this thesis to knowledge in the field of production and operations management is threefold: Firstly, a Multi-Agent System (MAS) is designed to directly apply pull production control to a good approximation of a real-life job-shop. The scale and complexity of the developed MAS prove that the application of pull production control in non-repetitive manufacturing systems is challenging, perplex and laborious. Secondly, the thesis examines three pull production control mechanisms namely, Kanban, Base Stock and Constant Work-in-Process (CONWIP) which it enhances so as to prevent system deadlocks, an issue largely unaddressed in the relevant literature. Having successfully tested the transferability of pull production control to non-repetitive manufacturing, the third contribution of this thesis is that it uses experimental and empirical data to examine the impact of pull production control on job-shop performance. The thesis identifies issues resulting from the application of pull control in job-shops which have implications for industry practice and concludes by outlining further research that can be undertaken in this direction

    Agent-Based Modeling: The Right Mathematics for the Social Sciences?

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    This study provides a basic introduction to agent-based modeling (ABM) as a powerful blend of classical and constructive mathematics, with a primary focus on its applicability for social science research.� The typical goals of ABM social science researchers are discussed along with the culture-dish nature of their computer experiments. The applicability of ABM for science more generally is also considered, with special attention to physics. Finally, two distinct types of ABM applications are summarized in order to illustrate concretely the duality of ABM: Real-world systems can not only be simulated with verisimilitude using ABM; they can also be efficiently and robustly designed and constructed on the basis of ABM principles. �

    On the relationship between strand spaces and multi-agent systems

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    Strand spaces are a popular framework for the analysis of security protocols. Strand spaces have some similarities to a formalism used successfully to model protocols for distributed systems, namely multi-agent systems. We explore the exact relationship between these two frameworks here. It turns out that a key difference is the handling of agents, which are unspecified in strand spaces and explicit in multi-agent systems. We provide a family of translations from strand spaces to multi-agent systems parameterized by the choice of agents in the strand space. We also show that not every multi-agent system of interest can be expressed as a strand space. This reveals a lack of expressiveness in the strand-space framework that can be characterized by our translation. To highlight this lack of expressiveness, we show one simple way in which strand spaces can be extended to model more systems

    Configuration management for multi-agent systems

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    As heterogeneous distributed systems, multi-agent systems present some challenging configuration management issues. There are the problems of knowing how to allocate agents to computers, launch them on remote hosts, and once the agents have been launched, how to monitor their runtime status so as to manage computing resources effectively. In this paper, we present the RETSINA Configuration Manager, RECoMa. We describe its architecture, how it uses agent infrastructure such as service discovery, to assist the multi-agent system administrator in allocating, launching, and monitoring a heterogeneous distributed agent system in a distributed and networked computing environment

    A trustworthy mobile agent infrastructure for network management

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    Despite several advantages inherent in mobile-agent-based approaches to network management as compared to traditional SNMP-based approaches, industry is reluctant to adopt the mobile agent paradigm as a replacement for the existing manager-agent model; the management community requires an evolutionary, rather than a revolutionary, use of mobile agents. Furthermore, security for distributed management is a major concern; agent-based management systems inherit the security risks of mobile agents. We have developed a Java-based mobile agent infrastructure for network management that enables the safe integration of mobile agents with the SNMP protocol. The security of the system has been evaluated under agent to agent-platform and agent to agent attacks and has proved trustworthy in the performance of network management tasks

    An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging

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    This paper proposes two new mixed integer programming models for capacitated multi-level lot-sizing problems with backlogging, whose linear programming relaxations provide good lower bounds on the optimal solution value. We show that both of these strong formulations yield the same lower bounds. In addition to these theoretical results, we propose a new, effective optimization framework that achieves high quality solutions in reasonable computational time. Computational results show that the proposed optimization framework is superior to other well-known approaches on several important performance dimensions
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