Governance of Autonomous Agents on the Web: Challenges and Opportunities

International audienceThe study of autonomous agents has a long tradition in the Multiagent System and the Semantic Web communities, with applications ranging from automating business processes to personal assistants. More recently, the Web of Things (WoT), which is an extension of the Internet of Things (IoT) with metadata expressed in Web standards, and its community provide further motivation for pushing the autonomous agents research agenda forward. Although representing and reasoning about norms, policies and preferences is crucial to ensuring that autonomous agents act in a manner that satisfies stakeholder requirements, normative concepts, policies and preferences have yet to be considered as first-class abstractions in Web-based multiagent systems. Towards this end, this paper motivates the need for alignment and joint research across the Multiagent Systems, Semantic Web, and WoT communities, introduces a conceptual framework for governance of autonomous agents on the Web, and identifies several research challenges and opportunities

Engineering Multi-Agent Systems: State of Affairs and the Road Ahead

The continuous integration of software-intensive systems together with the ever-increasing computing power offer a breeding ground for intelligent agents and multi-agent systems (MAS) more than ever before. Over the past two decades, a wide variety of languages, models, techniques and methodologies have been proposed to engineer agents and MAS. Despite this substantial body of knowledge and expertise, the systematic engineering of large-scale and open MAS still poses many challenges. Researchers and engineers still face fundamental questions regarding theories, architectures, languages, processes, and platforms for designing, implementing, running, maintaining, and evolving MAS. This paper reports on the results of the 6th International Workshop on Engineering Multi-Agent Systems (EMAS 2018, 14th-15th of July, 2018, Stockholm, Sweden), where participants discussed the issues above focusing on the state of affairs and the road ahead for researchers and engineers in this area

Organisation multi-agent pour la gouvernance de systèmes Machine-to-Machine

http://www.emse.fr/~picard/publications/persson11jfsma.pdfInternational audienceLe paradigme Machine-to-Machine (M2M) implique des appareils (capteurs, effecteurs) interagissant pour fournir des services localisés dans le monde physique. Avec la maturité du M2M, émerge une demande grandissante pour des solutions mutualisées dans lesquelles les applications peuvent partager un ensemble commun d'appareils. Dans ce contexte, le projet SensCity propose une infrastructure pour mettre en oeuvre des applications à l'échelle de la ville, ce qui nécessite de fournir des moyens de gouvernance agile pour prendre en compte l'extensibilité du système (ie. scalability). Nous proposons d'utiliser les technologies multi-agents pour répondre à cette problématique. Selon cette approche, la stratégie de gouvernance est exprimée par une organisation multi-agent à l'aide du framework organisationnel MOISE. Nous illustrons notre proposition par un système de gestion intelligente du strationnement

Multi-agent Self-organization and Reorganization to Adapt M2M Infrastructures

International audienceMachine-to-Machine (M2M) systems are based on networks of sensors and actuators immersed in the physical world, like in Smart Cities. To manage such networks, classical so-called vertical approaches (where one stakeholder is involved from services to sensors) are very expensive. Thus, a growing trend emerges for horizontal architectures, where several stakeholders collaborate within the same infrastructure. Moreover, the growing number of connected devices raises the key issue of properly controlling and adapting capabilities so that human intervention is minimized. Based on a Multi-Agent Oriented Programming approach, the Adaptive Governance MAS for M2M systems (AGaMeMnon) system installs such capabilities by combining self-organization and reorganization mechanisms. This will be the focus of this paper. AGaMeMnon has been implemented and linked to the SensCity project middleware and evaluated experimentally by the means of simulations

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019