Les simulations de propagation de feu en milieu urbain

40 pagesComment simuler la propagation d'un incendie ? Le feu est un phénomène complexe et son fonctionnement physico-chimique n'est pas complètement élucidé. Pour qu'une simulation soit non seulement crédible mais aussi prédictive, de nombreux phénomènes sont à prendre en considération, alors que ces informations ne sont pas nécessairement connues (géométrie exacte des lieux, composition chimique du combustible, etc.). Les modèles proposés ne s'appliquent correctement qu'à certains types d'incendies et doivent généralement être perfectionnés avant de pouvoir être adaptés à des situations particulières

A Model for Virtual Reconfigurable Modular Robots

This paper presents a model for virtual reconfigurable modular robots in order to evolve artificial creatures, able of self-adaptation to the environment as well as good adjustment to various given tasks. For this purpose, a simulator has been entirely developed with the assistance of a physics engine to represent force activities. One of the most crucial points in modular robot construction is the choice of module type, complexity and diversity. We took interest on existing elements to obtain realistic results but assume simplifications to focus on our main goal that is algorithmic

MecaCell: an Open-source Efficient Cellular Physics Engine

International audienceWe present an open source physics engine specialised for multi-cellular artificial organisms simulations. It is computationally efficient in comparison to gas-based and finite element models and more realistic than standard mass-spring-damper systems

Toward Organogenesis of Artificial Creatures

International audienceThis paper presents a new model for the development of artificial creatures from a single cell. The model aims at providing a more biologically plausible abstraction of the morphogenesis and the specialization process, which the organogenesis follows. It is built upon three main elements: a cellular physics simulation, a simplified cell cycle using an evolved artificial gene regulatory network and a cell specialization mechanism quantifying the ability to perform different functions. As a proof-of-concept, we present a first experiment where the morphology of a multicellular organism is guided by cell weaknesses and efficiency at performing different functions under environmental stress

L'apprentissage automatique comme base du suivi d'élèves et de l'amélioration de formations

National audienceCet article vise à présenter un projet de recherche dont le but est d'utiliser des méthodes d'intelligence artificielle et de fouille de données pour l'e-learning. Nous proposons des solutions techniques au problème du suivi des élèves en formation et de l'amélioration des formations proposées. Notre solution prend la forme d'une application qui centralisera des données issues de LMS et permettra de les examiner et de les analyser en utilisant des méthodes de l'intelligence artificielle. Cette application pourra dans un deuxième temps servir de base à la création d'un tuteur virtuel intelligent. Nous détaillons nos propositions concernant les méthodes à employer, l'architecture de l'application et les éléments choisis pour servir d'indicateurs et d'attributs d'apprentissage automatique, et analysons les résultats préliminaires d'un partitionnement de données

Self-organization of Symbiotic Multicellular Structures

International audienceThis paper presents a new model for the development of artificial creatures from a single cell. The model aims at providing a more biologically plausible abstraction of the morphogenesis and the specialization process, which the organogenesis follows. It is built upon three main elements: a cellular physics system that simulates division and intercellular adhesion dynamics, a simplified cell cycle offering to the cells the possibility to select actions such as division, quiescence, differentiation or apoptosis and, finally, a cell specialization mechanism quantifying the ability to perform different functions. An evolved artificial gene regulatory network is employed as a cell controller. As a proof-of-concept, we present two experiments where the morphology of a multicellular organism is guided by cell weaknesses and efficiency at performing different functions under environmental stress

Path Finding and Collision Avoidance in Crowd Simulation

Motion planning for multiple entities or a crowd is a challenging problem in today’s virtual environments. We describe in this paper a system designed to simulate pedestrian behaviour in crowds in real time, concentrating particularity on collision avoidance. On-line planning is also referred as the navigation problem. Additional difficulties in approaching navigation problem are that some environments are dynamic. In our model we adopted a popular methodology in computer games, namely A* algorithm. The idea behind A* is to look for the shortest possible routes to the destination not through exploring exhaustively all the possible combination but utilizing all the possible directions at any given point. The environment is formed in regions and the algorithm is used to find a path only in visual region. In order to deal with collision avoidance, priority rules are given to some entities as well as some social behaviour

Clustering Moodle data as a tool for profiling students

International audienceThis paper describes the first step of a research project with the aim of predicting students' performance during an online curriculum on a LMS and keeping them from falling behind. Our research project aims to use data mining, machine learning and artificial intelligence methods for monitoring students in e-learning trainings. This project takes the shape of a partnership between computer science / artificial intelligence researchers and an IT firm specialized in e-learning software. We wish to create a system that will gather and process all data related to a particular e-learning course. To make monitoring easier, we will provide reliable statistics, behaviour groups and predicted results as a basis for an intelligent virtual tutor using the mentioned methods. This system will be described in this article. In this step of the project, we are clustering students by mining Moodle log data. A first objective is to define relevant clustering features. We will describe and evaluate our proposal. A second objective is to determine if our students show different learning behaviours. We will experiment whether there is an overall ideal number of clusters and whether the clusters show mostly qualitative or quantitative differences. Experiments in clustering were carried out using real data obtained from various courses dispensed by a partner institute using a Moodle platform. We have compared several classic clustering algorithms on several group of students using our defined features and analysed the meaning of the clusters they produced

Splittable metamorphic carrier robots

International audienceMetamorphic modular robots are versatile systems composed of a set of independent modules. These modules are able to deliberately change their overall topology in order to adapt to new circumstances, perform new tasks, or recover from damage. The modules considered in this paper are cubic shapes, and we assume that each of them has a separate computational resources and it is equipped with a specialized sensors to perceive the environment. In this paper, we demonstrate the ability of these robots to evolve the topology of the whole structure in order to achieve, surround and transport target objects dispersed in the environment. While performing its task, the robot may be splitted into several parts in order to cope with environmental variations. Our work integrates a simplified model of biological hormone system to generate inputs for a finite-state machine (FSM) that controls the evolution process

Analysis of students clustering results based on Moodle log data

International audienceThis paper describes a proposal of relevant clustering features and the results of experiments using them in the context of determining students' learning behaviors by mining Moodle log data. Our clustering experiments tried to show whether there is an overall ideal number of clusters and whether the clusters show mostly qualitative or quantitative differences. They were carried out using real data obtained from various courses dispensed by a partner institute using a Moodle platform. We have compared several classic clustering algorithms on several group of students using our defined features and analysed the meaning of the clusters they produced