How to Prevent Intolerant Agents from High Segregation?

International audienceIn the framework of Agent-Based Complex Systems we examine dynamics that lead individuals towards spatial segregation. Such systems are constituted of numerous entities, among which local interactions create global patterns which cannot be easily related to the properties of the constituent entities. In the 70's, Thomas C. Schelling showed that an important spatial segregation phenomenon may emerge at the global level, if it is based upon local preferences. Moreover, segregation may occur, even if it does not correspond to agent preferences. In real life preferences regarding segregation are influenced by individual contexts as well as social norms; in this paper we will propose a model which describes the dynamic evolution of individuals tolerance. We will introduce heterogeneity in agents' preferences and allow them to evolve over time taking into account both the individuals tolerance and the neighbourhood's preferences. We will show that it is possible to dynamically get a distribution of tolerance over the agents with a low average and in the same time to deeply limit global aggregation. As the Schelling's model showed that individual tolerance can nevertheless induce global aggregation, this paper takes the opposite view showing that intolerant agents can avoid segregation in some extent

Eye-tracking and learning experience: gaze trajectories to better understand the behavior of memorial visitors

Eye-tracking technology is increasingly introduced in museums to assess their role in learning and knowledge transfer. However, their use provide limited quantitative and/or qualitative measures such as viewing time and/or gaze trajectory on an isolated object or image (Region of Interest "ROI"). The aim of this work is to evaluate the potential of the mobile eye-tracking to quantify the students’ experience and behaviors through their visit of the "Genocide and mass violence" area of the Caen memorial. In this study, we collected eye-tracking data from 17 students during their visit to the memorial. In addition, all visitors filled out a questionnaire before the visit, and a focus group was conducted before and after the visit. The first results of this study allowed us to analyze the viewing time spent by each visitor in front of 19-selected ROIs, and some of their specific sub-parts. The other important result was the reconstruction of the gaze trajectory through these ROIs. Our global trajectory approach allowed to complete the information obtained from an isolated ROI, and to identify some behaviors such as avoidance. Clustering analysis revealed some typical trajectories performed by specific sub-groups. The eye-tracking results were consolidated by the participants' answers during the focus group. &nbsp

Differences in Human Cortical Gene Expression Match the Temporal Properties of Large-Scale Functional Networks

International audienceWe explore the relationships between the cortex functional organization and genetic expression (as provided by the Allen Human Brain Atlas). Previous work suggests that functional cortical networks (resting state and task based) are organized as two large networks (differentiated by their preferred information processing mode) shaped like two rings. The first ring–Visual-Sensorimotor-Auditory (VSA)–comprises visual, auditory, somatosensory, and motor cortices that process real time world interactions. The second ring–Parieto-Temporo-Frontal (PTF)–comprises parietal, temporal, and frontal regions with networks dedicated to cognitive functions, emotions, biological needs, and internally driven rhythms. We found–with correspondence analysis–that the patterns of expression of the 938 genes most differentially expressed across the cortex organized the cortex into two sets of regions that match the two rings. We confirmed this result using discriminant correspondence analysis by showing that the genetic profiles of cortical regions can reliably predict to what ring these regions belong. We found that several of the proteins–coded by genes that most differentiate the rings–were involved in neuronal information processing such as ionic channels and neurotransmitter release. The systematic study of families of genes revealed specific proteins within families preferentially expressed in each ring. The results showed strong congruence between the preferential expression of subsets of genes, temporal properties of the proteins they code, and the preferred processing modes of the rings. Ionic channels and release-related proteins more expressed in the VSA ring favor temporal precision of fast evoked neural transmission (Sodium channels SCNA1, SCNB1 potassium channel KCNA1, calcium channel CACNA2D2, Synaptotagmin SYT2, Complexin CPLX1, Synaptobrevin VAMP1). Conversely, genes expressed in the PTF ring favor slower, sustained, or rhythmic activation (Sodium channels SCNA3, SCNB3, SCN9A potassium channels KCNF1, KCNG1) and facilitate spontaneous transmitter release (calcium channel CACNA1H, Synaptotagmins SYT5, Complexin CPLX3, and synaptobrevin VAMP2)

Optimal viable path search for a cheese ripening process using a multi-objective EA.

International audienceViability theory is a very attractive theoretical approach for the modeling of complex dynamical systems. However, its scope of application is limited due to the high computational power it necessitates. Evolutionary computation is a convenient way to address some issues related to this theory. In this paper, we present a multi-objective evolutionary approach to address the optimisation problem related to the computation of optimal command profiles of a complex process. The application we address here is a real size problem from dairy industry, the modeling of a Camembert cheese ripening process. We have developed a parallel implementation of a multiobjective EA that has produced a Pareto front of optimal control profiles (or trajectories), with respect to four objectives. The Pareto front was then analysed by an expert who selected a interesting compromise, yielding a new control profile that seems promising for industrial applications

Brainhack: a collaborative workshop for the open neuroscience community

International audienceBrainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science

Optimal viable path search for a cheese ripening process using a multi-objective EA.

International audienceViability theory is a very attractive theoretical approach for the modeling of complex dynamical systems. However, its scope of application is limited due to the high computational power it necessitates. Evolutionary computation is a convenient way to address some issues related to this theory. In this paper, we present a multi-objective evolutionary approach to address the optimisation problem related to the computation of optimal command profiles of a complex process. The application we address here is a real size problem from dairy industry, the modeling of a Camembert cheese ripening process. We have developed a parallel implementation of a multiobjective EA that has produced a Pareto front of optimal control profiles (or trajectories), with respect to four objectives. The Pareto front was then analysed by an expert who selected a interesting compromise, yielding a new control profile that seems promising for industrial applications

Describing the Result of a Classifier to the End-User: Geometric-based Sensitivity

International audienceThis paper addresses the issue of supporting the end-user of a classifier, when it is used as a decision support system, to classify new cases. We consider several kinds of classifiers: Statistical or machine learning classifiers, which are built on data, but also direct model-based classifiers that are built to solve a particular problem (like in viability or control problems). The end-user relies mainly on global information (like error rates or global sensitivity analysis) to assess the quality of the result given by the system. Class membership probability, if available, describes certainly the local statistical viewpoint. But it doesn't take into account other contextual information: Cases with high value of class membership probability can also be close to the decision boundary. In the case of numerical state space, we propose to use the decision boundary of the classifier (which always exists, even implicitly), to describe the situation of a particular case: The distance of a case to the decision boundary measures the robustness of the decision to a change in the input data. Other geometric concepts, such as the maximal maximal ball, can present a precise picture of the situation to the end-user. We show the interest of such a geometric study on different examples

The complex system science for optimal strategy of management of a food system: the camembert cheese ripening

International audienceSignificant advances are needed for food systems in terms of real-time prognosis capability developments, incorporating large scale modelling, distributed simulation and optimisation, and complete integration of the methods and algorithms. The goal is to be able to develop new paradigms at the frontier of life science and computing science for the management of systems like food systems. In parallel, just in the process of emerging and linked to these same questions is the science of complex systems, that proposes ways to understand systems located in turbulent, instable and changing environments. This paper points out and illustrates the interest to develop an approach adapting and coupling some fundamental tools of the complex system science. It combines viability and robustness analysis, multi-objective optimisation calculus and high computational performance using a computing grid. Adapted to the camembert cheese ripening, it has led to propose new strategies for control the process. One solution of the calculated pareto front, is compared to two trajectories tested during experiments led on a pilot, one standard and another optimized one. The total mass loss deviation for the calculated trajectory by comparison to the standard one is 0.04 kg in the same time and for identical microorganisms behaviour

Décrire le résultat d'un système discriminant à l'utilisateur : la sensibilité géométrique

International audienceThis paper addresses the issue of supporting the end-user of a classifier, when it is used as a decision support system, to classify new cases. We consider several kinds of classifiers: Statistical or machine learning classifiers, which are built on data, but also direct model-based classifiers that are built to solve a particular problem (like in viability or control problems). The end-user relies mainly on global information (like error rates or global sensitivity analysis) to assess the quality of the result given by the system. Class membership probability, if available, describes certainly the local statistical viewpoint. But it doesn't take into account other contextual information: Cases with high value of class membership probability can also be close to the decision boundary. In the case of numerical state space, we propose to use the decision boundary of the classifier (which always exists, even implicitly), to describe the situation of a particular case: The distance of a case to the decision boundary measures the robustness of the decision to a change in the input data. Other geometric concepts, such as the maximal maximal ball, can present a precise picture of the situation to the end-user. We show the interest of such a geometric study on different examples.Cet article propose une méthode, basée sur la géométrie, pour aider l'utilisateur d'un système discriminant à apprécier les résultats dans le cadre de l'aide à la décision