Chair objectives

The integrative challenge of AI is fully realized in human-robot interaction and more precisely in human-robot collaboration when humans and robots decide and act together and share the space and the task.

One key concept appears to be essential, the concept of joint action. To mention some key abilities, successful joint action requires joint attention, mutual manifestness to exhibit and maintain joint intention while refining and achieving a shared task collaboratively in order to facilitate the human partner understanding of the current state, of the
robot’s capabilities and predicting upcoming actions.

The scientific challenge here is to devise and build the cognitive and interactive abilities to allow pertinent, transparent, verifiable and legible behaviors for a robot that is able to perform collaborative activity with a human partner.

Such an architecture should integrate an incremental learning system that will allow the robot to acquire new abilities for human-robot collaboration while ensuring transparency, explainability and verifiability of the overall decisional abilities and their evolution over time.

Les dialogues multimodaux devraient être utilisés comme un moyen d’informer l’humain et assurer la cohérence. Le système sera ensuite évalué dans des contextes où il est utilisé pour mener des actions conjointes et/ou affiner des capacités avec des utilisateurs non-spécialistes.

Program Collaborative AI
Themes: Language, Neuroscience & AI, Robotics & AI

Chair holder: Rachid Alami, DR CNRS, Laas


François Félix Ingrand (CNRS Senior Scientist) 

Thierry Siméon (CNRS Senior Scientist) 

Website :

Know more

Man and robot face to face, with Rachid Alami

A pioneer in cognitive robotics, Rachid Alami has dedicated his career to intelligent robots and the improvement of human-machine interactions. Thanks to advances in artificial intelligence, it is helping to take a further step towards the synergy between humans and robots. 

Read the article in French


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