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20112023
most citedAn Application of Deep Reinforcement Learning to Algorithmic Trading

222 citations · 600 across the 46 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.LG2020★ 2 cited

QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning

Pascal Leroy, Damien Ernst, Pierre Geurts +3

This paper introduces four new algorithms that can be used for tackling multi-agent reinforcement learning (MARL) problems occurring in cooperative settings. All algorithms are bas…

eess.SY2020

Assessing the Impact of Offshore Wind Siting Strategies on the Design of the European Power System

David Radu, Mathias Berger, Antoine Dubois +5

This paper provides a detailed account of the impact of different offshore wind siting strategies on the design of the European power system. To this end, a two-stage method is pro…

eess.SY2020★ 1 cited

Allocation of locally generated electricity in renewable energy communities

Miguel Manuel de Villena, Samy Aittahar, Sebastien Mathieu +3

Local electricity markets represent a way of supplementing traditional retailing contracts for end consumers -- among these markets, the renewable energy community has gained momen…

cs.NE2020★ 26 cited

A bio-inspired bistable recurrent cell allows for long-lasting memory

Nicolas Vecoven, Damien Ernst, Guillaume Drion

Recurrent neural networks (RNNs) provide state-of-the-art performances in a wide variety of tasks that require memory. These performances can often be achieved thanks to gated recu…

q-fin.TR2020★ 1 cited

An Artificial Intelligence Solution for Electricity Procurement in Forward Markets

Thibaut Théate, Sébastien Mathieu, Damien Ernst

Retailers and major consumers of electricity generally purchase an important percentage of their estimated electricity needs years ahead in the forward market. This long-term elect…

cs.LG2020

Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent

Adrien Bolland, Ioannis Boukas, Mathias Berger +1

We consider the joint design and control of discrete-time stochastic dynamical systems over a finite time horizon. We formulate the problem as a multi-step optimization problem und…