Modélisation comportementale

Résumé

La modélisation comportementale est la modélisation du comportement, c'est-à-dire la détection et la mesure des éléments du comportement afin d'en réaliser un modèle mathématique. Elle peut concerner tant des systèmes physiques que des comportements humains individuels et collectifs et est utilisée notamment comme outil prévisionnel dans divers domaines d'activité. Autant cette modélisation peut être fiable pour prévoir et contrôler le comportement d'un système physique, autant les incertitudes affectant les comportements humains (distorsion des courbes probabilités, inversion de préférences, seuils d'émergence...) font que de tels modèles ne peuvent alors qu'être indicatifs. Historique Bibliographie

The embodiment of cockroach aggregation behavior in a group of micro-robots

Masoud Asadpour, Gilles Caprari, Simon Garnier

We report the faithful reproduction of the self-organized aggregation behavior of the German cockroach Blattella germanica with a group of robots. We describe the implementation of the biological model provided by Jeanson et al. in Alice robots, and we compare the behaviors of the cockroaches and the robots using the same experimental and analytical methodology. We show that the aggregation behavior of the German cockroach was successfully transferred to the Alice robot despite strong differences between robots and animals at the perceptual, actuatorial, and computational levels. This article highlights some of the major constraints one may encounter during such a work and proposes general principles to ensure that the behavioral model is accurately transferred to the artificial agents.

2008

Chargement

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Synaptic plasticity, a key process for memory formation, manifests itself across different time scales ranging from a few seconds for plasticity induction up to hours or even years for consolidation and memory retention. We developed a three-layered model of synaptic consolidation that accounts for data across a large range of experimental conditions. Consolidation occurs in the model through the interaction of the synaptic efficacy with a scaffolding variable by a read-write process mediated by a tagging-related variable. Plasticity-inducing stimuli modify the efficacy, but the state of tag and scaffold can only change if a write protection mechanism is overcome. Our model makes a link from depotentiation protocols in vitro to behavioral results regarding the influence of novelty on inhibitory avoidance memory in rats.

Society for Neuroscience2015

Chargement

Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio

Frank Bonnet, Bertrand Eric Collignon, Francesco Mondada, Vaios Papaspyros

Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed groups of sensor-rich robots and animals and study collective interactions from the within a bio-hybrid group. In recent work, scientists showed that a robot-controlled lure is capable of influencing the collective decisions of zebrafish Danio rerio shoals moving in a ring and a two-room setup. Here, we study a closely related topic, that is, the collective behavior patterns that emerge when different behavioral models are reproduced through the use of a robotic lure. We design a behavioral model that alternates between obeying and disobeying the collective motion decisions in order to become socially accepted by the shoal members. Subsequently, we compare it against two extreme cases: a reactive and an imposing decision model. For this, we use spatial, directional and information theoretic metrics to measure the degree of integration of the robotic agent. We show that our model leads to similar information flow as in freely roaming shoals of zebrafish and exhibits leadership skills more often than the open-loop models. Thus, in order for the robot to achieve higher degrees of integration in the zebrafish shoal, it must, like any other shoal member, be bidirectionally involved in the decision making process. These findings provide insight on the ability to form mixed societies of animals and robots and yield promising results on the degree to which a robot can influence the collective decision making.

2019

Chargement