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Vers un modèle biologiquement plausible de la sélection de l'action pour un robot mobile

Abstract : This thesis aims at studying the different mechanisms involved in action selection and de- cision making processes, according to animal experiments and neurobiological recordings. For that matter, we propose several biologically plausible models for action selection. The goal is to achieve a better understanding of the animal’s brain functions. This gives us the opportunity to develop bioinspired control architectures for robots that are more robust and adaptative to a real environement. These models are based on Artificial Neural Networks, allowing us to test our hypotheses on simulations of different brain regions and function, implemented on robots and virtual agents. Action selection for mobile robots can be approached from different angles. This process can be seen as the selection between two possibilities, e.g. go left or go right. Those mechanisms involve the ability to learn and categorize specific events, encoding contexts where a change in the perception is perceived, a change in the behavior is noticed or the decision is made. There- fore, this thesis studies those capacities of acquisition, categorisation and coding of different events that can be relevant for action selection. We also, approach the action selection as a strategy selection. The different behaviors are guided consciously or through automated behavior learned as habits. We investigate different possibilities allowing a robot to develop those capacities. Also, we aim at studying interactions that can emerge between those mechanisms during navigational behaviors. The work presented in this these is based on the modelisation of the hippocampo-cotico- basal loops involved in the navigational behaviors, the action selection and the multimodal cat- egorisation of events. We base our models on a previous model of the hippocampus for the learning of spatio-temporal associations and for multimodal conditionning of perceptive events. It is based on sensorimotor associations between place cells and actions to achieve navigational behaviors. The model involves also a specific type of hippocampic cells, named transition cells, for temporal prediction of future events. This capacity allows the model to learn spatio-temporal sequences, and it represents the neural substrate for the learning of a cognitive map, hypoth- esised to be localized in prefrontal and/or parietal areas. This kind of topological map allows to plan the behavior of the robot according to its motivations, which is used in goal oriented experiments to achieve goals and capture rewards
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Contributor : Souheïl Hanoune <>
Submitted on : Sunday, December 13, 2015 - 3:03:56 PM
Last modification on : Thursday, March 5, 2020 - 4:25:48 PM
Document(s) archivé(s) le : Monday, March 14, 2016 - 4:42:09 PM


  • HAL Id : tel-01242624, version 1



Souheïl Hanoune. Vers un modèle biologiquement plausible de la sélection de l'action pour un robot mobile. Autre. Université de Cergy-Pontoise, 2015. Français. ⟨tel-01242624⟩



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