Inria’s Exploratory Actions: taking risks

Changed on 18/03/2021

The purpose of Exploratory Actions is to facilitate the emergence of new research themes and to give scientists the resources they need to test original ideas. These trial runs can then be extended through the creation of an Inria project team. 

Illustration Actions exploratoires Inria : prendre des risques
© Inria / Photo C. Morel

Putting trust in scientists and their intuition

Exploratory actions provide an opportunity to put trust in the intuition of researchers. Through this scheme, Inria is able to focus resources on a number of subjects that are highly innovative, risky and potentially disruptive with regard to the institute's traditional approaches - in artificial intelligence, in e-health and in digital agriculture. It provides a way of delving deeper into individual subjects and proving their relevance from a scientific perspective: an essential step prior to launching the creation of a new project team. This might also involve exploring themes that are unusual for Inria or which are normally steered clear of, including subjects relating to social sciences or law.

ugénie Brasier et Raphaël James utilisent le mur d'écran Wilder
Plateforme Wilder - © Inria / Photo C. Morel

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Our exploratory actions

AI4HI: Artificial Intelligence for Human Intelligence

AYANA: Télédétection et IA embarqués pour le ”New Space"

CGB: Réseaux et communautés agroécologiques

COML: The Cognitive Machine Learning Team

DARE: Data Repurposing

DATA4US: Transparence des données personnelles pour les internautes

ELAN: Modélisation de l'apparence des phénomènes non linéaires

ETHICAM: Nouveaux paradigmes de communication basés sur des technologies émergentes

EXODE: Passage à l'échelle des solveurs d'EDO pour la biologie computationnelle

GRAM: Programmation chimique de vésicules artificielles

KOPERNIC: Adapter le raisonnement pire cas à différentes criticités

MALESI: MAchine LEarning for Simulation

ODiM: Outils informatisés d’aide au Diagnostic des Maladies mentales

OptiTrust: Produire du code haute performance digne de confiance

Réal: Réécriture algébrique

RSG: Risques Systémiques Globaux

SNIDE: Search Non neutratlIty Detection

SR4SG: Sequential collaborative learning of recommandations for sustainable gardening

TRACME: Trajectoires causales multiéchelles