4 citations · 10 across the 8 of their papers we have counts for
8 papers
From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models
Eleni Nisioti, Claire Glanois, Elias Najarro +7
Large Language Models (LLMs) have taken the field of AI by storm, but their adoption in the field of Artificial Life (ALife) has been, so far, relatively reserved. In this work we…
ACES: Generating Diverse Programming Puzzles with with Autotelic Generative Models
Julien Pourcel, Cédric Colas, Gaia Molinaro +2
The ability to invent novel and interesting problems is a remarkable feature of human intelligence that drives innovation, art, and science. We propose a method that aims to automa…
Augmenting Autotelic Agents with Large Language Models
Cédric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer +2
Humans learn to master open-ended repertoires of skills by imagining and practicing their own goals. This autotelic learning process, literally the pursuit of self-generated (auto)…
A Song of Ice and Fire: Analyzing Textual Autotelic Agents in ScienceWorld
Laetitia Teodorescu, Xingdi Yuan, Marc-Alexandre Côté +1
Building open-ended agents that can autonomously discover a diversity of behaviours is one of the long-standing goals of artificial intelligence. This challenge can be studied in t…
Automatic Exploration of Textual Environments with Language-Conditioned Autotelic Agents
Laetitia Teodorescu, Eric Yuan, Marc-Alexandre Côté +1
In this extended abstract we discuss the opportunities and challenges of studying intrinsically-motivated agents for exploration in textual environments. We argue that there is imp…
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…
SpatialSim: Recognizing Spatial Configurations of Objects with Graph Neural Networks
Laetitia Teodorescu, Katja Hofmann, Pierre-Yves Oudeyer
Recognizing precise geometrical configurations of groups of objects is a key capability of human spatial cognition, yet little studied in the deep learning literature so far. In pa…
Deep Sets for Generalization in RL
Tristan Karch, Cédric Colas, Laetitia Teodorescu +2
This paper investigates the idea of encoding object-centered representations in the design of the reward function and policy architectures of a language-guided reinforcement learni…