298 citations · 650 across the 27 of their papers we have counts for
50 papers
Emergent Communication: Generalization and Overfitting in Lewis Games
Mathieu Rita, Corentin Tallec, Paul Michel +4
Lewis signaling games are a class of simple communication games for simulating the emergence of language. In these games, two agents must agree on a communication protocol in order…
vec2text with Round-Trip Translations
Geoffrey Cideron, Sertan Girgin, Anton Raichuk +3
We investigate models that can generate arbitrary natural language text (e.g. all English sentences) from a bounded, convex and well-behaved control space. We call them universal v…
KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal
Tadashi Kozuno, Wenhao Yang, Nino Vieillard +10
In this work, we consider and analyze the sample complexity of model-free reinforcement learning with a generative model. Particularly, we analyze mirror descent value iteration (M…
On the role of population heterogeneity in emergent communication
Mathieu Rita, Florian Strub, Jean-Bastien Grill +2
Populations have often been perceived as a structuring component for language to emerge and evolve: the larger the population, the more structured the language. While this observat…
Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act
Alexis Jacq, Johan Ferret, Olivier Pietquin +1
Traditionally, Reinforcement Learning (RL) aims at deciding how to act optimally for an artificial agent. We argue that deciding when to act is equally important. As humans, we dri…
RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning
Sabela Ramos, Sertan Girgin, Léonard Hussenot +9
We introduce RLDS (Reinforcement Learning Datasets), an ecosystem for recording, replaying, manipulating, annotating and sharing data in the context of Sequential Decision Making (…