Rémy Courdier

Environment as support for simplification, reuse and integration of processes in spatial MAS

The development of solutions to complex problems requires finding answers to several questions which are obstacles on the road leading to the solution. To perpetuate progress, the possibility to reuse and integrate these intermediate answers in the other constructions of complex solution becomes a requirement In this article we consider the context of spatial multi-agent systems and we propose a modeling method that allows to structure models in order to make their components autonomous and, thus, to allow their reuses and their integrations in the design of future models. This method is based on the definition of a principle that permits to differentiate the model components, and, on the use of the environment (which is the location in which agents evolve) as the coupling element of these components

Towards an emergence machine for complex systems simulations

This paper presents a simulation platform that has been realised in Java 1.1 for the study of behaviour and evolutionary processes in non-linear systems. To support the modelling of such systems, we propose the use of agent technology as high level tool to design applications. The framework enables to study emergence by exploiting distributing computing as key issues of the system behaviour. Applications developed with the platform are then simulated to adequately capture any behaviour likely to be observed, to exhibit self organised structures, and to emphasise complex processes, which are brought in action. This approach then allows the study of macroscopic collections endowed with the potential to evolve during time.

GEAMAS V2.0: an object oriented platform for complex systems simulations

This paper presents the object oriented design and implementation of GEAMAS V2.0, a toolkit for virtual simulations of complex systems. GEAMAS V2.0 is structured in three modules: the kernel, the generation environment and the simulation environment. The kernel implements an object model for agents and provides generic classes. The generation environment allows the graphical design of applications. The simulation environment enables the observation of the simulations evolution via graphical user interface tools. The implementation uses Java 1.1. We applied GEAMAS V2.0 to the sand-pile automaton problem. This reference application, which is easily modeled with GEAMAS V2.0, provides a first validation of our system architecture and simulation mechanism.

An Ontology for Observation of Multiagent Based Simulation

In multiagent based simulation (MABS), the observation of simulation results is a complex task: interactions between simulation agents produce a large mass of simulation results, which is particularly complex to analyze. We are assured that the use of another second multiagent system is a suitable approach to achieve this task. This second system then introduces a new category of agents called observation agents. The first step to build this multiagent system for observation is to define a specification of concepts used between its observation agents. Our contribution is an ontology for observation of MABS. This ontology is composed of a set of concepts and relations usable to acquire and process simulation results, and to produce their presentation form. This ontology has three main root classes: observation elements, processing, and presentation

Integration of generic motivations in social hybrid agents

Most hybrid agent architectures are constructed with a hierarchical succession of reactive (at a lower level) and cognitive (at a higher level) layers. Each of these layers represents a behavior, a function, a decision, etc. Instead of using such functional layers, we propose in this paper a generic model of a social hybrid agent, which is based on natural (human/animal) motivations of the agent. We discuss here the contribution of our approach in hybrid agent modeling. The present work uses the American psychologist Abraham Maslow’s pyramid of needs. The basis of this modeling uses the result of an existing psychological study.

OBJECT-BASED KNOWLEDGE AND REASONING DESIGNED FOR DIAGNOSTICS

Abstract In this paper, we present a knowledge based system which seems to be particulary adapted to support the special mechanisms required by fault diagnosis systems. This article presents the data representation used to describe the knowledge base and the architecture of a deductive machine implemented to operate on this complex knowledge structure. This inference engine is based on object-oriented software representation approach and determines inference strategies on knowledge bases represented as a semantic network. The last part of the paper describes the different kinds of knowledge incorporated in the system and shows how they are formalised

A multiagent system to model human action based on the concept of affordance

This paper presents a model to represent situated action in farming systems. The basic idea is to invert the classical vision of action that stipulates that action is a consequence of a decision process and a plan. We consider action as mainly dictated by a situation created by the interaction of the actor and his/her environment. Hence, action is a process that emerges from this situation. Thus, in this paper we treat the question of how to model action as an emergence process from the situations created by actors and their environment? For this, our model is based on multiagent system as well as on the affordance, emergence and stigmergy concepts (this paper emphasizes mainly the first two).

Modelling Situated Action Based on Affordances and Stigmergy

This paper describes a model to represent human activities in farming systems based on the situated action theory. The idea is to consider the environment as an intelligent entity that has the ability to decide locally, at given time and space, the actions to perform. Surrogates of real actors, called actuators, just execute the actions dictated by the agents embedded in the environment. The model is based on the affordance and stigmergy concepts as well as a multi-agents modelling approach.

Ordonnancement parallèle de simulations orientées agent Une approche basée sur l'analyse des dépendances temporelles des influences et perceptions.

Representation of temporal concepts impacts simulation models and their execution performances. Large-Scale Agent-based Simulations require resources that can be mainly found in distributed systems. We propose to extend our work on the Temporality model used to represent temporal concepts in our platform GEAMAS-NG. This enables us to parallelize simulation execution on a plaforms network while warrantying causality between simulated events.

MASC: Map Sectors Creator a tool to help at the configuration of multi-agents systems for everyone

The initialization at the beginning of all type of simulation is recurring. In the field of multi-agents, spatial environments on a micro or macro scale, or more abstract context, such as mapping out energy sources for example, need often to be modelled. The initialization of these environments wherein evolve agents is generally tedious and time-consuming depending on the fineness of the mesh of the cutting in case of a 2D spatial representation. In this paper, we present MASC (Map Sectors Creator), a user-oriented tool that permits easy initialization through the creation of a mesh directly usable in multi-agents systems simulations platforms. The automation of cutting out maps followed by the generation of directly usable code snippets optimize the working time on initialization and allow to focus on the simulations results and observations.