Methods for Agent-Based Computer Modelling

International audiencePlenary Session of the Tam Dao University

Moral Guilt : An Agent-Based Model Analysis

International audienceIn this article we analyze the influence of a concrete moral emotion (i.e. moral guilt) on strategic decision making. We present a normal form Prisoner’s Dilemma with a moral component. We assume that agents evaluate the game’s outcomes with respect to their ideality degree (i.e. how much a given outcome conforms to the player’s moral values), based on two proposed notions on ethical preferences: Harsanyi’s and Rawls’. Based on such game, we construct and agent-based model of moral guilt, where the intensity of an agent’s guilt feeling plays a determinant role in her course of action. Results for both constructions of ideality are analyzed

A new BDI agent architecture based on the belief theory. Application to the modelling of cropping plan decision-making

Agent-based simulations are now widely used to study complex systems. However, the problem of the agent design is still an open issue, especially for social ecological models, where some of the agents represent human beings. In fact, designing complex agents able to act in a believable way is a difficult task, in particular when their behaviour is led by many conflicting needs and desires. A widely used way to formalise the internal architecture of such complex agents is the BDI (Belief Desire-Intention) paradigm. This paradigm allows to design expressive and realistic agents, yet, it is rarely used in simulation context. A reason is that most agent architectures based on the BDI paradigm are complex to understand by non-computer-scientists. Moreover, they are often very time-consuming in terms of computation. In this paper, we propose a new architecture based on the BDI paradigm that copes with these two issues. In our architecture, the choice of the most relevant action by an agent is based on the belief theory. We present an application of our agent architecture to an actual model dedicated to cropping plan decision-making. This application that takes into plays thousands of farmer agents shows promising results

Une architecture d'agent BDI basée sur la théorie des fonctions de croyance : application à la simulation du comportement des agriculteurs

National audienceLa simulation à base d'agents est maintenant largement utilisée pour étudier les systèmes complexes. Cependant, le problème de la définition des agents est toujours posé. Définir des agents complexes capables d'agir de manière réaliste est une tâche difficile. Un paradigme couramment utilisé pour formaliser le comportement de tels agents est le paradigme BDI (Belief-Desire-Intention). Cependant, ce formalisme est peu utilisé en simulation. Une raison est que la plupart des architectures basées sur celui-ci sont très complexes à comprendre pour des non informaticiens. De plus, elles sont en générales très lourdes en termes de temps de calcul. Dans cet article, nous proposons ici une architecture agent basée sur le paradigme BDI et sur la théorie des fonctions de croyance qui permet de répondre aux difficultés précitées. Nous présentons une application de celle-ci pour la simulation du choix et de la conduite de systèmes de culture par des agriculteurs. Cette application montre que notre architecture permet de faire tourner plusieurs milliers d'agents simultanément

Combination Framework of BI solution & Multi-agent platform (CFBM) for multi-agent based simulations

International audienceIntegrated environmental modeling in general and specifically Multi-agent-based modeling and simulation approach are increasingly used in decision-support systems with, as a major consequence, to manipulate and generate a huge amount of data for their functioning (parametrization, use of real data in the simulation, ...). Therefore there is a need to manage efficiently these data being either used or generated by the simulation. Practically, existing general-ist simulation platforms lack database access and analysis tools and simulation outputs are usually stored as text files or spreadsheets to be manipulated later by dedicated tools. In this paper, we propose a solution to handle simulation models data, i.e. their outputs as well as corresponding real data. We designed a conceptual framework based on a combination of two components, a Business Intelligence (BI) solution and a multi-agent platform. Such a framework aims at managing simulation models data throughout the lifespan of the simulation, from its execution and its coupling with real data to the generation of simulation results order to use the simulation model as an effective decision-support sys-tem with what-if scenarios

Des données géographiques à la simulation à base d'agents : application de la plate-forme GAMA

International audienceCes dernières années, la simulation à base d’agents a révélé certains intérêts en géographie. Néanmoins, s’il existe aujourd’hui de nombreuses plates-formes permettant de faciliter le développement de modèle, celles-ci sont souvent trop complexes pour être utilisées par des non-informaticiens (par exemple Repast Symphony) ou trop limitées pour développer des modèles riches intégrant de nombreux agents et données (par exemple Netlogo). La plate-forme GAMA a pour objectif d’offrir aux modélisateurs une plate-forme à la fois puissante et simple d’accès grâce à langage de modélisation dédié. Dans cet article, nous présentons les capacités particulièrement avancées de la nouvelle version de la plate-forme GAMA pour la gestion de l’espace. Cette plate-forme permet en particulier de gérer simultanément plusieurs environnements basés sur trois types de topologie (continue, grille, graphe), d’intégrer très simplement des données géographiques (vectorielles et rasters) et de représenter des géométries dans un environnement 3D. Les capacités détaillées dans cet article sont illustrées par un modèle sur les problématiques de ségrégation urbaine

The logic of acceptance: grounding institutions on agents' attitudes

International audienceIn the recent years, several formal approaches to the specification of normative multi-agent systems and artificial institutions have been proposed. The aim of this paper is to advance the state of the art in this area by proposing an approach in which a normative multi-agent system is conceived to be autonomous, in the sense that it is able to create, maintain, and eventually change its own institutions by itself, without the intervention of an external designer in this process. In our approach the existence and the dynamics of an institution (norms, rules, institutional facts, etc.) are determined by the (individual and collective) acceptances of its members, and its dynamics depends on the dynamics of these acceptances. In order to meet this objective, we propose the logic AL (Acceptance Logic) in which the acceptance of a proposition by the agents qua members of an institution is introduced. Such propositions are true w.r.t. an institutional context and correspond to facts that are instituted in an attitude-dependent way. The second part of the paper is devoted to the logical characterization of some important notions in the theory of institutions. We provide a formalization of the concept of constitutive rule, expressed by a statement of the form "X counts as Y in the context of institution x". Then, we formalize the concepts of obligation and permission (so called regulative rules). In our approach constitutive rules and regulative rules of a certain institution are attitude-dependent facts which are grounded on the acceptances of the members of the institution

On The Joint Modeling of The Behavior of Social Insects and Their Interaction With Environment by Taking Into Account Physical Phenomena Like Anisotropic Diffusion

International audienceThis work takes place in the framework of GEODIFF project (funded by CNRS) and deals with the general issue of the social behavior modeling of pest insects with a particular focus on Bark Beetles. Bark Beetles are responsible for pine trees devastation in North America since 2005. In order to stem the problem and to apply an adapted strategy, one should be able to predict the evolution of the population of Bark Beetles. More precisely, a model taking into account a given population of insects (a colony) interacting with its environment, the forest ecosystem, would be very helpful. In a previous work, we aimed to model diffusive phenomenons across the environment using a simple reactive Multi-agent System. Bark beetle use pheromones as a support for recruitment of other bark beetles in the neighborhood in order to achieve a mass attack over a tree. They are first attracted by the ethanol or other phytopheromones emitted by a sick, stressed or dead tree and reinforce the presence of other individuals amongst the targeted tree. Both ethanol and semiochemicals are transported through the forest thanks to the wind, thermic effects and this advection phenomenon is modulated by the topology of the environment, tree and other obstacles distribution. In other words, the environment is involved in the process of a bark beetle attack. The first modeling we used to tackle our objective was not spatially explicit as long as free space propagation only was taken into account (isotropic phenomenon) with no constraint imposed by the environment such as wind. This article is intended to take into account such physical phenomenons and push the modeling one step further by providing predictions driven by measures provided by a Geographical Information System