The design of an agent based model of human activities and communications in cardiac resuscitation

International audienceCardio-pulmonary arrest is a common emergency situation causing over 400,000 deaths per year, more than a 1000 per day, in the USA alone. The goal of this work is to develop an agent based computer simulator that will allow trainers to experiment with different communication protocols, such as those found in air traffic control. This paper describes the first step in designing the simulator development. The design is based on an analysis of communications during real life training simulations using the FIPA standard categories

Un modèle à base d'agents pour prédire les trajectoires des piétons dans des espaces partagés avec un véhicule autonome

International audienceThis paper addresses modeling and simulating pedestrian trajectories when interacting with an autonomous vehicle in a shared space. Pedestrian motion models integrating pedestrians interactions with an autonomous vehicle already exist. However, they fail to accurately predict the individual trajectory of each pedestrian, and they do not deal with the diversity of possible pedestrian interactions with the vehicle in a shared space (front, back or lateral). Moreover, previous works do not sufficiently provide a quantitative evaluation of the model's predictions. In this paper, we propose an hybrid pedestrian model that combines the social force model and a new decision model for conflicting pedestrian-vehicle interactions. The proposed model integrates different observed pedestrians behaviors, as well as the behaviors of the social groups of pedestrians. We validate the model and evaluate its predictive potential through qualitative and quantitative comparisons with ground truth trajectories. The proposed model reproduces observed behaviors that have not been replicated by the social force model and outperforms the social force model at predicting pedestrians trajectories on the used dataset. This model will be used by an autonomous vehicle in a shared space to predict the trajectories of surrounding pedestrians

Computationnal cognitive modelling of children's text reading

L'apprentissage de la lecture nécessite notamment d'acquérir une coordination fine des mouvements des yeux, de l’attention et des traitements lexicaux afin de permettre une lecture fluide et efficace. Contrairement à ce que nous ressentons, le comportement des yeux est très complexe et dépend de plusieurs facteurs liés aux propriétés du langage, aux connaissances lexicales, à l’expertise en lecture de l’individu et à la nature de la tâche. L’étude des différences interindividuelles entre les experts, les bons et les faibles lecteurs peut nous aider à mieux comprendre les processus sous – jacents de la lecture.Le contrôle fin des mouvements des yeux peut être étudié en recourant à des analyses statistiques ou à des modèles computationnels qui simulent les processus de la lecture et reproduisent des mouvements oculaires, spatialement et temporellement. Dans ces travaux de thèse, nous avons utilisé les analyses statistiques et la modélisation computationnelle pour comprendre pourquoi nous observons des différences dans les comportements en lecture entre différents groupes d’âge (adultes vs enfants) et au sein du même groupe d’âge (faibles vs bons lecteurs). Ainsi, les changements observés entre ces différents groupes peuvent être expliqués par des différences dues à l’effet du développement du contrôle oculomoteur et/ou des compétences en lecture. Une question fondamentale est la compréhension de la cause et de l’effet de ces changements au niveau des mouvements des yeux.Ainsi, les questions cruciales auxquelles nous tenterons de répondre sont les suivantes: quelles sont les différences au niveau des comportements oculomoteurs entre les différents groupes d’âge des lecteurs (adultes vs enfants) ? Pourquoi observons- nous ces différences ? Pour un public ciblé d’enfants, quelles sont les caractéristiques des comportements oculaires sur les mots, en termes de fixations, de saccades ? Comment en rendre compte dans une démarche de modélisation des processus oculomoteurs de la lecture ?Learning to read requires the coordination of eye movements, attention, as well as lexical processing in order to achieve smooth reading. Contrary to what we perceive, the behavior of our eyes is very complex and depends on several factors linked to the properties of the language, the lexical knowledge, the reading skills and the goal of the task. The study of interindividual differences could help us to better understand the reading processes.The eye movement control during reading could be analyzed with statistical methods and with computational models which can simulate the reading processes spatially and temporally. In this work, we used both methods in order to better understand why we observe differences in the reading patterns between different groups of readers of different ages (adults vs children) and of the same age (poor and good readers). The observed changes between different groups could be explained by differences in the oculomotor development and/or by differences in lexical knowledge. One fundamental question is to understand the causes of these changes at the level of eye movement control.The crucial questions that we tried to investigate in this work are the following: what are the differences in terms of eye movements between different groups of reading age? Why do we observe these differences? What are the patterns of eye movements for different groups of poor and good readers of the same age? How can we simulate the observed patterns with computational modeling of reading

Modélisation cognitive computationnelle de la lecture de textes chez les enfants

Learning to read requires the coordination of eye movements, attention, as well as lexical processing in order to achieve smooth reading. Contrary to what we perceive, the behavior of our eyes is very complex and depends on several factors linked to the properties of the language, the lexical knowledge, the reading skills and the goal of the task. The study of interindividual differences could help us to better understand the reading processes.The eye movement control during reading could be analyzed with statistical methods and with computational models which can simulate the reading processes spatially and temporally. In this work, we used both methods in order to better understand why we observe differences in the reading patterns between different groups of readers of different ages (adults vs children) and of the same age (poor and good readers). The observed changes between different groups could be explained by differences in the oculomotor development and/or by differences in lexical knowledge. One fundamental question is to understand the causes of these changes at the level of eye movement control.The crucial questions that we tried to investigate in this work are the following: what are the differences in terms of eye movements between different groups of reading age? Why do we observe these differences? What are the patterns of eye movements for different groups of poor and good readers of the same age? How can we simulate the observed patterns with computational modeling of reading?L'apprentissage de la lecture nécessite notamment d'acquérir une coordination fine des mouvements des yeux, de l’attention et des traitements lexicaux afin de permettre une lecture fluide et efficace. Contrairement à ce que nous ressentons, le comportement des yeux est très complexe et dépend de plusieurs facteurs liés aux propriétés du langage, aux connaissances lexicales, à l’expertise en lecture de l’individu et à la nature de la tâche. L’étude des différences interindividuelles entre les experts, les bons et les faibles lecteurs peut nous aider à mieux comprendre les processus sous – jacents de la lecture.Le contrôle fin des mouvements des yeux peut être étudié en recourant à des analyses statistiques ou à des modèles computationnels qui simulent les processus de la lecture et reproduisent des mouvements oculaires, spatialement et temporellement. Dans ces travaux de thèse, nous avons utilisé les analyses statistiques et la modélisation computationnelle pour comprendre pourquoi nous observons des différences dans les comportements en lecture entre différents groupes d’âge (adultes vs enfants) et au sein du même groupe d’âge (faibles vs bons lecteurs). Ainsi, les changements observés entre ces différents groupes peuvent être expliqués par des différences dues à l’effet du développement du contrôle oculomoteur et/ou des compétences en lecture. Une question fondamentale est la compréhension de la cause et de l’effet de ces changements au niveau des mouvements des yeux.Ainsi, les questions cruciales auxquelles nous tenterons de répondre sont les suivantes: quelles sont les différences au niveau des comportements oculomoteurs entre les différents groupes d’âge des lecteurs (adultes vs enfants) ? Pourquoi observons- nous ces différences ? Pour un public ciblé d’enfants, quelles sont les caractéristiques des comportements oculaires sur les mots, en termes de fixations, de saccades ? Comment en rendre compte dans une démarche de modélisation des processus oculomoteurs de la lecture

The design of an agent based model of human activities and communications in cardiac resuscitation

International audienceCardio-pulmonary arrest is a common emergency situation causing over 400,000 deaths per year, more than a 1000 per day, in the USA alone. The goal of this work is to develop an agent based computer simulator that will allow trainers to experiment with different communication protocols, such as those found in air traffic control. This paper describes the first step in designing the simulator development. The design is based on an analysis of communications during real life training simulations using the FIPA standard categories

Understanding communications in medical emergency situations

International audienceGood communication is essential within teams dealing with emergency situations. In this paper we look at communications within a resuscitation team performing cardio-pulmonary resuscitation. Communication underpins efficient collaboration, joint coordination of work, and helps to construct a mutual awareness of the situation. Poor communication wastes valuable time and can ultimately lead to life-threatening mistakes. Although training sessions frequently focus on medical knowledge and procedures, soft skills, such as communication receive less attention. This paper analyses communication problems in the case of CPR and proposes an architecture that merges a situation awareness model and the belief-desire-intention (BDI) approach in multi-agent systems. The architecture forms the basis of an agent-based simulator used to assess communication protocols in CPR teams

Multi-agent geospatial simulation of human interactions and behaviour in bushfires.

International audienceUnderstanding human behaviour and interactions in risk situations may help to improve crisis management strategies in order to avoid the worst scenarios. In this paper we present a geospatial agent-based model and simulation of human behaviour in bushfires. We have modelled the social interactions between different actors involved in bushfires such as firefighter, police, emergency centre managers and civilians. We use the Belief, Desire and Intention (BDI) architecture to model realistic human behaviour, and the FIPA-ACL standard to model the communications. We use geospatial data to represent the environment in a realistic way. We show how the model has been implemented and how we have unified the communications model and the BDI architecture. Finally, we compare the processing time of two implementations of our model representing a 2D simple and a 3D GIS environment

Agent-Based Modeling for Predicting Pedestrian Trajectories Around an Autonomous Vehicle

International audienceThis paper addresses modeling and simulating pedestrian trajectories when interacting with an autonomous vehicle in a shared space. Most pedestrian-vehicle interaction models are not suitable for predicting individual trajectories. Data-driven models yield accurate predictions but lack generalizability to new scenarios, usually do not run in real time and produce results that are poorly explainable. Current expert models do not deal with the diversity of possible pedestrian interactions with the vehicle in a shared space and lack microscopic validation. We propose an expert pedestrian model that combines the social force model and a new decision model for anticipating pedestrian-vehicle interactions. The proposed model integrates different observed pedestrian behaviors, as well as the behaviors of the social groups of pedestrians, in diverse interaction scenarios with a car. We calibrate the model by fitting the parameters values on a training set. We validate the model and evaluate its predictive potential through qualitative and quantitative comparisons with ground truth trajectories. The proposed model reproduces observed behaviors that have not been replicated by the social force model and outperforms the social force model at predicting pedestrian behavior around the vehicle on the used dataset. The model generates explainable and real-time trajectory predictions. Additional evaluation on a new dataset shows that the model generalizes well to new scenarios and can be applied to an autonomous vehicle embedded prediction

An analysis of reading skill development using E-Z Reader

International audiencePreviously reported simulations using the E-Z Reader model of eye-movement control suggest that the patterns of eye movements observed with children versus adult readers reflect differences in lexical processing proficiency. However, these simulations fail to specify precisely what aspect(s) of lexical processing (e.g., orthographic processing) account for the concurrent changes in eye movements and reading skill. To examine this issue, the E-Z Reader model was first used to simulate the aggregate eye-movement data from 15 adults and 75 children to replicate the finding that gross differences in reading skill can be accounted for by differences in lexical processing proficiency. The model was then used to simulate the eye-movement data of individual children so that the best-fitting lexical processing parameters could be correlated to measures of orthographic knowledge, phonological processing skill, sentence comprehension, and general intelligence. These analyses suggest that orthographic knowledge accounts for variance in the eye-movement measures that is observed with between-individual differences in reading skill. The theoretical implications of this conclusion will be discussed in relation to computational models of reading and our understanding of reading skill development