78 citations · 216 across the 24 of their papers we have counts for
11 papers · 1 filter
Contrastive Multimodal Learning for Emergence of Graphical Sensory-Motor Communication
Tristan Karch, Yoann Lemesle, Romain Laroche +2
In this paper, we investigate whether artificial agents can develop a shared language in an ecological setting where communication relies on a sensory-motor channel. To this end, w…
Social Network Structure Shapes Innovation: Experience-sharing in RL with SAPIENS
Eleni Nisioti, Mateo Mahaut, Pierre-Yves Oudeyer +2
Human culture relies on innovation: our ability to continuously explore how existing elements can be combined to create new ones. Innovation is not solitary, it relies on collectiv…
Language and Culture Internalisation for Human-Like Autotelic AI
Cédric Colas, Tristan Karch, Clément Moulin-Frier +1
Building autonomous agents able to grow open-ended repertoires of skills across their lives is a fundamental goal of artificial intelligence (AI). A promising developmental approac…
Socially Supervised Representation Learning: the Role of Subjectivity in Learning Efficient Representations
Julius Taylor, Eleni Nisioti, Clément Moulin-Frier
Despite its rise as a prominent solution to the data inefficiency of today's machine learning models, self-supervised learning has yet to be studied from a purely multi-agent persp…
Grounding Spatio-Temporal Language with Transformers
Tristan Karch, Laetitia Teodorescu, Katja Hofmann +2
Language is an interface to the outside world. In order for embodied agents to use it, language must be grounded in other, sensorimotor modalities. While there is an extended liter…
Grounding Artificial Intelligence in the Origins of Human Behavior
Eleni Nisioti, Clément Moulin-Frier
Recent advances in Artificial Intelligence (AI) have revived the quest for agents able to acquire an open-ended repertoire of skills. However, although this ability is fundamentall…
Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration
Cédric Colas, Tristan Karch, Nicolas Lair +4
Developmental machine learning studies how artificial agents can model the way children learn open-ended repertoires of skills. Such agents need to create and represent goals, sele…
A correlational analysis of multiagent sensorimotor interactions: clustering autonomous and controllable entities
M. Sánchez-Fibla, C. Moulin-Frier, X. Arsiwalla +1
A first step to reach Theory of Mind (ToM) abilities (attribution of beliefs to others) in synthetic agents through sensorimotor interactions, would be to tag sensory data with age…
DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self
Clément Moulin-Frier, Tobias Fischer, Maxime Petit +16
This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative…
Embodied Artificial Intelligence through Distributed Adaptive Control: An Integrated Framework
Clément Moulin-Frier, Jordi-Ysard Puigbò, Xerxes D. Arsiwalla +2
In this paper, we argue that the future of Artificial Intelligence research resides in two keywords: integration and embodiment. We support this claim by analyzing the recent advan…
Decision Making under Uncertainty: A Quasimetric Approach
Steve N'Guyen, Clément Moulin-Frier, Jacques Droulez
We propose a new approach for solving a class of discrete decision making problems under uncertainty with positive cost. This issue concerns multiple and diverse fields such as eng…