Distributed enterprise search using software agents

In this paper we introduce a distributed information retrieval system using agent-based technology. In this multiagent system, each agent has its own specific task and can be used to handle a specific document repository. The system is designed to automatically comply with access restriction rules that are normally enforced in companies. It is used in the administration offices of the German capital city Berlin where it serves as a testbed for further research on aggregated search in an enterprise environment with roughly 50,000 employees

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

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

Privacy in Cooperative Distributed Systems: Modeling and Protection Framework

A new form of computation is emerging rapidly with cloud computing, mobile computing, wearable computing and the Internet-of-Things. All can be characterized as a class of “Cooperative Distributed Systems” (CDS) in open environment. A major driver of the growth is the exponential adoption by people and organizations within all aspects of their day-to-day matters. In this context, users’ requirements for privacy protection are becoming essential and complex beyond the traditional approaches. This requires a formal treatment of “privacy” as a fundamental computation concept in CDS paradigm. The objective is to develop a comprehensive formal model for “privacy” as base to build a CDS based framework and platform in which various applications allow users to enjoy the comprehensive services in open environments while protecting their privacy seamlessly. To this end, this thesis presents a novel way of understudying, modeling and analyzing privacy concerns in CDS. A formal foundations and model of privacy is developed within the context of information management. This served as a base for developing a privacy protection management framework for CDS. It includes a privacy-aware agent model for CDS platform with the ability to support interaction-based privacy protection. The feasibility of the proposed models has been demonstrated by developing an agent-based CDS platform using JIAC framework and a privacy-based Contract Net Protocol. It also included the application scenarios for the framework for privacy protection is Internet-of-Tings, cloud-based resource scheduling and personal assistance

Agents Cut Emissions On how a Multi-Agent System Contributes to a more Sustainable Energy Consumption

AbstractThe Vehicle-to-Grid technology allows electric vehicles to not only procure electric energy, but also to feed energy back into the grid network. However, by using Vehicle-to-Grid, energy literally degenerates into an article of merchandise and becomes of interest to several stakeholders. In this paper, we describe a multi-agent system, which embraces this exact view and maximises the interest of several stakeholders in using Vehicle-to-Grid capable electric vehicles. In order to emphasise the applicability of our approach we performed a field test with real electric vehicles and charging stations. We describe both, implementational details as well as the results of our field test in this paper

Chapter Leveraging Internet-of-Things to Support Circular Economy Paradigm in Manufacturing Industry

Circular economy represents a fundamental alternative to the currently predominating linear economy model, while Industry 4.0 is a technological enabler to bring process innovation in the industrial domain. New economic models are needed in order to reduce material inputs and waste generation leveraging on ecodesign, recycling and reusing of products, new business models, and new technologies. Internet-of-Things and artificial intelligence can support the circular economy paradigm, through the development of a marketplace for connecting buyers and sellers of manufacturing services, raw materials and products toward building global supply chains. The core component of this marketplace is a novel, agent-based, brokering module that will apply both syntactic and semantic matching in terms of manufacturing capabilities, in order to find the best possible supplier to fulfill a request for a service, raw materials or products involved in the supply chain

Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computerscientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones

Process control and configuration of a reconfigurable production system using a multi-agent software system

Thesis (M. Tech. (Information Technology)) -- Central University of technology, Free State, 2011Traditional designs for component-handling platforms are rigidly linked to the product being produced. Control and monitoring methods for these platforms consist of various proprietary hardware controllers containing the control logic for the production process. Should the configuration of the component handling platform change, the controllers need to be taken offline and reprogrammed to take the changes into account. The current thinking in component-handling system design is the notion of re-configurability. Reconfigurability means that with minimum or no downtime the system can be adapted to produce another product type or overcome a device failure. The re-configurable component handling platform is built-up from groups of independent devices. These groups or cells are each responsible for some aspect of the overall production process. By moving or swopping different versions of these cells within the component-handling platform, re-configurability is achieved. Such a dynamic system requires a flexible communications platform and high-level software control architecture to accommodate the reconfigurable nature of the system. This work represents the design and testing of the core of a re-configurable production control software platform. Multiple software components work together to control and monitor a re-configurable component handling platform. The design and implementation of a production database, production ontology, communications architecture and the core multi-agent control application linking all these components together is presented

Leveraging Internet-of-Things to Support Circular Economy Paradigm in Manufacturing Industry

Circular economy represents a fundamental alternative to the currently predominating linear economy model, while Industry 4.0 is a technological enabler to bring process innovation in the industrial domain. New economic models are needed in order to reduce material inputs and waste generation leveraging on ecodesign, recycling and reusing of products, new business models, and new technologies. Internet-of-Things and artificial intelligence can support the circular economy paradigm, through the development of a marketplace for connecting buyers and sellers of manufacturing services, raw materials and products toward building global supply chains. The core component of this marketplace is a novel, agent-based, brokering module that will apply both syntactic and semantic matching in terms of manufacturing capabilities, in order to find the best possible supplier to fulfill a request for a service, raw materials or products involved in the supply chain

Unifying JIAC Agent Development with AWE

Abstract. In this paper we describe the Agent World Editor, a tool for designing multi-agent systems and generating executable agent code. The tool also unifies the handling of different agent frameworks through an abstract agent model and an extensible transformation infrastructure. Currently, the tool supports three different agent frameworks of the JIAC family, and we feel confident that the approach holds for other frameworks as well as for the generation of multi-agent systems on heterogenous platforms