Communication Between Process and Structure: Modelling and Simulating Message Reference Networks with COM/TE

Focusing on observable message signs and referencing structures, communication processes can be described and analysed as message reference networks which are characterized by dynamic pattern evolution. Computational simulation provides a way of obtaining insights into the factors driving such processes. Our paper describes a theoretical framework for communication-oriented modelling — the COM approach — that is centred around the notion of social visibility as a reputation mechanism. The approach contrasts with agent-based social networks on the one hand, and with bibliometric document networks on the other. In introducing our simulation environment COM/TE, typical properties of message reference networks are discussed in terms of a case study which deals with the impact of different media and styles of communication on emergent patterns of social visibility.Communication, Communication-Oriented Modelling, Message Sign, Dynamic Networks, Bottom-up Approach, Temporality, Social Visibility, Reputation, Socionics

Multi-Agents Systems and Territory: Concepts, Methods and Applications

This paper analyses the multi-agents systems that are now considered the best tool to simulate and study real world. We review the main characteristics of a multi-agents system, namely interactions and cooperations of agents, communications and behaviours between them and finally the schedule of actions and jobs assignment to agents. The multi-agents system approach is increasingly applied in social and economic sciences; so we study mainly the territorial applications. In these applications new characteristics arise from the consideration of territory (land and space where the agents live or territory as an agent in itself, that evolves in the time). We study possible new applications of multi-agents applied to the territory (for instance, to define town planning policies or to locate dangerous facilities). Furthermore we study new tools to make operational multi-agents systems (mainly Swarm, the toolkit of Santa Fe Institute). With Swarm we present two kind of territorial applications: with located agents (fixed in space) and with not located agents (moving in the space). Finally we show the results of these applications.

Economics of intelligent selection of wireless access networks in a market-based framework : a game-theoretic approach

The Digital Marketplace is a market-based framework where network operators offer communications services with competition at the call level. It strives to address a tussle between the actors involved in a heterogeneous wireless access network. However, as with any market-like institution, it is vital to analyze the Digital Marketplace from the strategic perspective to ensure that all shortcomings are removed prior to implementation. In this paper, we analyze the selling mechanism proposed in the Digital Marketplace. The mechanism is based on a procurement first-price sealed-bid auction where the network operators represent the sellers/bidders, and the end-user of a wireless service is the buyer. However, this auction format is somewhat unusual as the winning bid is a composition of both the network operator’s monetary bid and their reputation rating. We create a simple economic model of the auction, and we show that it is mathematically intractable to derive the equilibrium bidding behavior when there are N network operators, and we make only generic assumptions about the structure of the bidding strategies. We then move on to consider a scenario with only two network operators, and assume that network operators use bidding strategies which are linear functions of their costs. This results in the derivation of the equilibrium bidding behavior in that scenario

A Reputation-Based Approach to Self-Adaptive Service Selection

Service-orientation provides concepts and tools for flexible composition and management of largescale distributed software applications. The automated run-time management of such loosely coupled software systems, however, poses still major challenges and is therefore an active research area, including the use of novel computing paradigms. In this context, the dynamic and adaptive selection of best possible service providers is an important task, which can be addressed by an appropriate middleware layer that allows considering different service quality aspects when managing the adaptive execution of distributed service workflows dynamically. In such an approach, service consumers are enabled to delegate the adaptive selection of service providers at run-time to the execution infrastructure. The selection criteria used are based on the cost of a service provision and the continuous, dynamic evaluation of reputations of providers, i.e. maintained track records of meeting the respective service commitments. This paper discusses the design and operating principle of such an automatic service selection middleware extension. Its ability to balance different quality criteria for service selection, such as service cost vs. the reliability of provision, is empirically evaluated based on a multi-agent platform approach

Android Malware Characterization using Metadata and Machine Learning Techniques

Android Malware has emerged as a consequence of the increasing popularity of smartphones and tablets. While most previous work focuses on inherent characteristics of Android apps to detect malware, this study analyses indirect features and meta-data to identify patterns in malware applications. Our experiments show that: (1) the permissions used by an application offer only moderate performance results; (2) other features publicly available at Android Markets are more relevant in detecting malware, such as the application developer and certificate issuer, and (3) compact and efficient classifiers can be constructed for the early detection of malware applications prior to code inspection or sandboxing.Comment: 4 figures, 2 tables and 8 page

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

Self-interested service-oriented agents based on trust and QoS for dynamic reconfiguration

Progressively increasing complexity of dynamic environments, in which services and applications are demanded by potential clients, requires a high level of reconfiguration of the offer to better match that ever changing demand. In particular, the dynamic change of the client’s needs, leading to higher exigency, may require a smart and flexible automatic composition of more elementary services. By leveraging the service-oriented architectures and multi-agent system benefits, the paper proposes a method to explore the flexibility of the decision support for the services’ reconfiguration based on several pillars, such as trust, reputation and QoS models, which allows the selection based on measuring the expected performance of the agents. Preliminary experimental results, extracted from a real case scenario, allow highlighting the benefits of the proposed distributed and flexible solution to balance the workload of service providers in a simple and fast manner. The proposed solution includes the agents’ intelligent decision-making capability to dynamically and autonomously change services selection on the fly, towards more trustworthy services with better quality when unexpected events happen, e.g. broken machines. We then propose the use of competitive self-interested agents to provide services that best suits to the client through dynamic service composition.info:eu-repo/semantics/publishedVersio