Bimodal traffic regulation system: A multi-agent approach

International audienceThe development of surface public transportation networks is a major issue in terms of ecology, economy and society. Their quality in terms of punctuality and passengers services (regularity between buses) should be improved in order to improve their attractiveness. To do so, cities often use regulation systems at intersections that grant priority to buses. The problem is that each transportation mode has its own characteristics and a dedicated decision support system. Therefore, most of them hardly take into account both public transport vehicles such as buses and private vehicle traffic. This paper proposes a multi-agent model that supports bimodal regulation and preserves monomodal regulation. The objective is to improve global traffic, to reduce bus delays and to improve bus regularity in congested areas of the network. In our approach, traffic regulation is obtained thanks to communication, collaboration and negotiation between heterogeneous agents. We tested our strategy on a complex network of nine junctions. The results of the simulation are presented

A Multi-Agent Method for Forming and Dynamic Restructuring of Pareto Optimal Coalitions

International audienceThe first part of this paper presents a coalition formation method for multi-agent systems which finds a Pareto optimal solution without aggregating the preferences of the agents. This protocol is adapted to problems requiring coordination by coalition formation, where it is undesirable, or not possible, to aggregate the preferences of the agents. The second part proposes an extension of this method enabling dynamic restructuring of coalitions when changes occur in the system

Coordination of supply chain activities: a coalition-based approach.

Companies operate in an environment increasingly demanding in terms of flexibility and reactivity. The introduction of the entities resulting from Distributed Artificial Intelligence (DAI) and Multi-Agent Systems (MAS) in the management of enterprises prove to be an interesting technology to simulate and reproduce the collaborative and adaptive behaviors of enterprises. This article models the coordination of the various collaborative parties both inside and outside a supply chain using coordination methods of MAS mainly coalition formation mechanisms. In this paper, we present our agent modeling of supply chains, and then we detail the coalition formation algorithm. Lastly, we illustrate our approach with an example chosen in the industrial domain.Distributed Artificial Intelligence (DAI); Multi-Agent System (MAS);

Meta-modele et heuristiques de jugement : le systeme CREDEX, application a l'evaluation du risque credit entreprise

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Les communications multi-parties et leur régulation dans les systèmes multi-agents (modèle et support)

Dans cette thèse, nous proposons une modélisation des communications multi-parties et leur régulation dans les systèmes multi-agents. Cette modélisation, appelée EASI (Environnement Actif comme Support des Interactions) est celle d'un environnement actif. Les agents lui déléguent les tâches d'adressage des données et de recherche d'information. La formalisation est issue de l'analyse de données symboliques, adaptée à ce type de problèmes. Les apports de ce modèle sont (1) la prise en compte du contexte pour mener à bien les tâches de l'environnement, et (2) la standardisation des interactions directes, fondées sur la sélection dynamique des récepteurs, et des interactions indirectes, fondées sur la sélection dynamique des messages. Nous généralisons ensuite le modèle pour réguler et contrôler les communications, en proposant le modèle EARI (Environnement Actif comme Régulateur de l'Interaction). L'environnement met en oeuvre des politiques d'interactions différenciées en fonction des comportements souhaités: services de communications standard et/ou règles impératives. Les agents peuvent également accroître ou restreindre leur attention (awareness) aux messages des autres agents. Les modèles sont complétés par des algorithmes de traitement et de mise à jour des informations, et par une architecture fonctionnelle de l'environnement. Ils ont été mis en oeuvre et évalués dans deux contextes de déploiement, un prototype en fonctionnement client/serveur et une extension de la plate-forme MadKit. Les tests réalisés ont montré un gain d'efficacité important de nos algorithmes sur le modèle généralement utilisé pour les communication multi-parties, la diffusionIn this Ph.d thesis, we propose a model of multi-party communications and their control for multi-agent systems. This model, called EASI (Environment as Active Support of Interaction) is that of an active environment. The agents delegate to it their data addressing and information search tasks. The formalization comes from Symbolic Data Analysis, which is suitable for this kind of problems. The contributions are (1) the use of the context to carry through the tasks of the environment, and (2) the standardization of direct interactions, based on the dynamic choice of the receivers, and indirect interactions, based on the dynamic selection of data. We extend our model to regulate and control the communications, with the EARI (Environment as Active Regulator of the Interaction) model. The environment carries out different communication policies, depending on the desired behavior: standard communication services and/or mandatory rules. The agents can also increase or decrease their awareness of other agents' messages. The models are completed with algorithms for data management and update and by an abstract architecture. They have been applied and evaluated in two different deployment contexts, a client/server prototype and an extension of the MadKit platform. The evaluation of our algorithms show a significant improvement in efficiency compared to the usual means of supporting multi-party communications, broadcastPARIS-DAUPHINE-BU (751162101) / SudocSudocFranceF

ESAC (MODELE D'INTERACTION, L'ENVIRONNEMENT COMME SUPPORT ACTIF DE COMMUNICATION. APPLICATION A LA GESTION DES TRANSPORTS URBAINS)

PARIS-DAUPHINE-BU (751162101) / SudocNANCY-INRIA Lorraine LORIA (545472304) / SudocSudocFranceF