Fabien Badeig

Environment as active support of interaction

Indirect interactions have been shown to be of interest in MultiAgent Systems (MAS), in the simulation area as well as in real applications. The environment is also emerging as a first-order abstraction. Intuitively, the environment being a common medium for the agents, it should be a suitable paradigm to provide an infrastructure for both direct and indirect interactions. However, it still lacks of a consensus on how the two relate to each other, and how the environment can support effectively notions as communication or awareness. We propose a general and operational model, Environment as Active Support of Interaction, that enables the agents to actively participate in the definition of their perceptions. Then, we show how the model provides a suitable framework for the regulation of the MAS interactions.

Contextual activation for Agent-Based Simulation

When designing agent-based simulation, thechoice of a coordination model is a key issue, since oneof the difficulties is to link the activation of the agentswith their context efficiently. Current solutions separatethe activation phase from the action phase of theagents, and each action phase is based on local agentcontext analysis which is time-expensive. Moreover, becausethe link between the context and the action is aninternal part of the agent, it is more difficult to modifythe way the agent reacts to the context without alteringthe way the agent is implemented. Our proposal, calledEASS (Environment as Active Support for Simulation),is a new approach for agent activation, where the contextis analysed inside the environment and conditionsthe activation of the agents. The main result of contextualactivation is to simplify the achievement of complexsimulations and to decrease run-time. The EASS modelhas been implemented within the kernel of MadKit, amulti-agent platform, and the first results are given.

Agent-based coordination model for designing transportation applications

This paper presents an environment-centered approach to design multi-agent solutions to transportation problems. Based on the property-based coordination principle (PbC), the objective of our approach is to solve three recurrent issues in the design of these solutions: the knowledge problem, the space-time dimension and the dynamics of the real environment. To demonstrate the benefits of our approach, two completely different applications, a demand-responsive transportation system and a simulator for crisis management, both based on this principle are presented. For each of them, we show how these recurrent issues have been solved.

Définition d'un cadre de conception et d'exécution pour la simulation multi-agent

La simulation multi-agent est utilisee pour comprendre des systemes complexes par la reproduction de divers scenarios. Dans les plates-formes de simulation actuelles, la politique d’ordonnancement consiste a controler l’activation sequentielle des agents qui executent systematiquement la boucle perception - decision - action. Cette approche centree agent est peu efficace en termes de temps d’execution et de conception. Nous proposons un nouveau cadre conceptuel et operationnel EASS dans lequel les agents mutualisent, au sein de l’environnement, les informations et les traitements necessaires a la mise en œuvre de la politique d’ordonnancement. Cette externalisation dans l’environnement d’une partie de l’activite des agents liee a leurs activations permet l’activation contextuelle. Les principaux avantages de l’activation contextuelle sont un gain d’efficacite en termes de temps d’execution, et une meilleure flexibilite de la gestion des comportements des agents en termes de conception.

Analyzing multi-agent approaches for the design of advanced interactive and collaborative systems

The purpose of this paper is to determine a set of requirements and proposals for the design of a collaborative inter- active system working under distributed tangible environments. A wide range of human-machine, human-human and human- environment interactions is to be considered, and using multi-agent architectures was recommended since they have already shown their benefits in developing large and complex systems under a unified framework. We further argue that such a design would require an in-depth analysis of four main properties (autonomy, proactiveness, context-awareness, situatedness). In this context, the potential interest and complementarity of two main design approaches (holonic and normative) are discussed. To support this discussion, two applications are also described - a Road Traffic simulation and a version of the game of RISK .B oth of these applications introduce complementary man-machine-environment interaction issues.

Un système multi-agent normatif hybride pour l’interaction mixte

Nous presentons une approche pour la conception d’un systeme multi-agent de preparation des acteurs communaux a la gestion de crises, dans le contexte d’une interaction via des tables tangibles distribuees. Notre point focal est celui des normes qui regissent ces interventions. Le role du systeme est d’analyser la validite des interventions au sens de ces normes et de transmettre des feedbacks appropries. La perspective normative permet une modelisation unifiee des 3 facettes (production, coordination et communication) de la collaboration. Nous presentons les premieres etapes de conception, qui s’appuie sur la plateforme JaCaMo, ainsi qu’un exemple d’application a des scenarios simples.

Evaluation of Environment Contextual Services in Multiagent Systems

The environment is a powerful first-order abstraction in Multi-Agent Systems (MAS), as well as a critical building block. The agents interact in their environment and the effects of their actions are observed and evaluated through this environment. The local complexity of the agents depends on its management of the interaction and action processes. If the environment carries out a part of this processes, the complexity of the agents is reduced. This delegating process implies a centralization of a part of the MAS computations inside the environment and therefore a flexible way to exchange information and to coordinate the agents.

Evaluating the cost of Supporting interaction and simulation through the environment

The environment has emerged as a powerful first-order abstraction in Multi-Agent Systems (MAS), as well as a critical building block. One benefit is to reduce the complexity of the agents by delegating to the environment a part of the tasks of the system. This delegating process provides a flexible way to exchange information and to coordinate the agents thanks to the environment. The counterpart is a centralization of a part of the MAS processes inside the environment. In this paper, we present the modeling of an environment for multi-agent communication and simulation. Our proposition enables the addition of advanced features to the MAS like multi-party communications (communication) and contextual activation (simulation). We evaluate the cost of this environment process and compare it to the execution of the same tasks in the agents for communication and simulation.