23 citations · 27 across the 5 of their papers we have counts for
5 papers
The Hive Mind is a Single Reinforcement Learning Agent
Karthik Soma, Yann Bouteiller, Heiko Hamann +1
Decision-making is an essential attribute of any intelligent agent or group. Natural systems are known to converge to effective strategies through at least two distinct mechanisms:…
Evolution of Societies via Reinforcement Learning
Yann Bouteiller, Karthik Soma, Giovanni Beltrame
The universe involves many independent co-learning agents as an ever-evolving part of our observed environment. Yet, in practice, Multi-Agent Reinforcement Learning (MARL) applicat…
From the Lab to the Theater: An Unconventional Field Robotics Journey
Ali Imran, Vivek Shankar Varadharajan, Rafael Gomes Braga +6
Artistic performances involving robotic systems present unique technical challenges akin to those encountered in other field deployments. In this paper, we delve into the orchestra…
The Portiloop: a deep learning-based open science tool for closed-loop brain stimulation
Nicolas Valenchon, Yann Bouteiller, Hugo R. Jourde +4
Closed-loop brain stimulation refers to capturing neurophysiological measures such as electroencephalography (EEG), quickly identifying neural events of interest, and producing aud…
Reinforcement Learning with Random Delays
Simon Ramstedt, Yann Bouteiller, Giovanni Beltrame +2
Action and observation delays commonly occur in many Reinforcement Learning applications, such as remote control scenarios. We study the anatomy of randomly delayed environments, a…