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Unravelling socio-motor biomarkers in schizophrenia

Publications associées (36)

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Optimization for Reinforcement Learning: From a single agent to cooperative agents

Volkan Cevher

Fueled by recent advances in deep neural networks, reinforcement learning (RL) has been in the limelight because of many recent breakthroughs in artificial intelligence, including defeating humans in games (e.g., chess, Go, StarCraft), self-driving cars, s ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Learning Control

Sylvain Calinon

This chapter presents an overview of learning approaches for the acquisition of controllers and movement skills in humanoid robots. The term learning control refers to the process of acquiring a control strategy to achieve a task. While the definition is i ...

Springer2019

Efficient Variance-Reduced Learning Over Multi-Agent Networks

Ali H. Sayed, Bicheng Ying, Kun Yuan

This work develops a fully decentralized variance-reduced learning algorithm for multi-agent networks where nodes store and process the data locally and are only allowed to communicate with their immediate neighbors. In the proposed algorithm, there is no ...

IEEE COMPUTER SOC2018

Model-based reinforcement learning and navigation in animals and machines

Dane Sterling Corneil

For decades, neuroscientists and psychologists have observed that animal performance on spatial navigation tasks suggests an internal learned map of the environment. More recently, map-based (or model-based) reinforcement learning has become a highly activ ...

EPFL2018

Learning Control

Sylvain Calinon

Springer2018

Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning

Rachid Guerraoui, El Mahdi El Mhamdi, Alexandre David Olivier Maurer, Hadrien Hendrikx

In reinforcement learning, agents learn by performing actions and observing their outcomes. Sometimes, it is desirable for a human operator to \textit{interrupt} an agent in order to prevent dangerous situations from happening. Yet, as part of their learni ...

EPFL2017

Bio-inspired balance controller for a humanoid robot

Auke Ijspeert, Renaud Ronsse, Nicolas Benoît Dominique Van der Noot, François André Heremans

Humanoid robots are gaining much interest nowadays. This is partly motivated by the ability of such robots to replace humans in dangerous environments being specifically designed for humans, such as man-made or natural disaster scenarios. However, existing ...

Ieee2016

Learning Search Strategies from Human Demonstrations

Guillaume Pierre Luc De Chambrier

Decision making and planning with partial state information is a problem faced by all forms of intelligent entities. The formulation of a problem under partial state information leads to an exorbitant set of choices with associated probabilistic outcomes m ...

EPFL2016

Control of agent swarms in random environments

Guillaume Adrien Sartoretti

The collective dynamic behavior of large groups of interacting autonomous agents (swarms) have inspired much research in both fundamental and engineering sciences. It is now widely acknowledged that the intrinsic nonlinearities due to mutual interactions c ...

EPFL2016

Triggering social interactions: chimpanzees respond to imitation by a humanoid robot and request responses from it

Aude Billard

Even the most rudimentary social cues may evoke affiliative responses in humans and promote socialcommunication and cohesion. The present work tested whether such cues of an agent may also promotecommunicative interactions in a nonhuman primate species, by ...

Springer Verlag2014