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A Deep Reinforcement Learning Framework for Continuous Intraday Market
  Bidding

A Deep Reinforcement Learning Framework for Continuous Intraday Market Bidding

Machine-mediated learning (ML), 2020
13 April 2020
Ioannis Boukas
D. Ernst
Thibaut Théate
Adrien Bolland
A. Huynen
Martin Buchwald
Christelle Wynants
Bertrand Cornélusse
ArXiv (abs)PDFHTML

Papers citing "A Deep Reinforcement Learning Framework for Continuous Intraday Market Bidding"

15 / 15 papers shown
Feature-driven reinforcement learning for photovoltaic in continuous intraday trading
Feature-driven reinforcement learning for photovoltaic in continuous intraday trading
Arega Getaneh Abate
Xiufeng Liu
Ruyu Liu
Xiaobing Zhang
145
0
0
15 Oct 2025
Gym-TORAX: Open-source software for integrating reinforcement learning with plasma control simulators in tokamak research
Gym-TORAX: Open-source software for integrating reinforcement learning with plasma control simulators in tokamak research
Antoine Mouchamps
Arthur Malherbe
Adrien Bolland
Damien Ernst
AI4CE
84
1
0
13 Oct 2025
Model Predictive Control-Guided Reinforcement Learning for Implicit Balancing
Model Predictive Control-Guided Reinforcement Learning for Implicit Balancing
Seyed soroush Karimi madahi
Kenneth Bruninx
Bert Claessens
Chris Develder
114
2
0
06 Oct 2025
Joint Bidding on Intraday and Frequency Containment Reserve Markets
Joint Bidding on Intraday and Frequency Containment Reserve Markets
Yiming Zhang
Wolfgang Ridinger
David Wozabal
88
0
0
03 Oct 2025
Bridging the Performance Gap Between Target-Free and Target-Based Reinforcement Learning
Bridging the Performance Gap Between Target-Free and Target-Based Reinforcement Learning
Théo Vincent
Yogesh Tripathi
Tim Lukas Faust
Yaniv Oren
Jan Peters
Carlo DÉramo
Jan Peters
Carlo DÉramo
CLL
349
3
0
04 Jun 2025
Advancing Investment Frontiers: Industry-grade Deep Reinforcement
  Learning for Portfolio Optimization
Advancing Investment Frontiers: Industry-grade Deep Reinforcement Learning for Portfolio Optimization
Philip Ndikum
Serge Ndikum
388
11
0
27 Feb 2024
Behind the Myth of Exploration in Policy Gradients
Behind the Myth of Exploration in Policy Gradients
Adrien Bolland
Gaspard Lambrechts
Damien Ernst
467
3
0
31 Jan 2024
Distributional Reinforcement Learning-based Energy Arbitrage Strategies
  in Imbalance Settlement Mechanism
Distributional Reinforcement Learning-based Energy Arbitrage Strategies in Imbalance Settlement Mechanism
Seyed soroush Karimi madahi
Bert Claessens
Chris Develder
227
9
0
23 Dec 2023
Domain-adapted Learning and Imitation: DRL for Power Arbitrage
Domain-adapted Learning and Imitation: DRL for Power Arbitrage
Yuanrong Wang
Vigneshwaran Swaminathan
Nikita P. Granger
Carlos Ros Perez
C. Michler
315
1
0
19 Jan 2023
Reinforcement Learning in Practice: Opportunities and Challenges
Reinforcement Learning in Practice: Opportunities and Challenges
Yuxi Li
OffRL
347
26
0
23 Feb 2022
Parameter-free Reduction of the Estimation Bias in Deep Reinforcement
  Learning for Deterministic Policy Gradients
Parameter-free Reduction of the Estimation Bias in Deep Reinforcement Learning for Deterministic Policy GradientsNeural Processing Letters (NPL), 2021
Baturay Saglam
Furkan B. Mutlu
Dogan C. Cicek
Suleyman S. Kozat
OffRL
148
8
0
24 Sep 2021
Application of deep reinforcement learning for Indian stock trading
  automation
Application of deep reinforcement learning for Indian stock trading automation
Supriya Bajpai
AIFin
158
10
0
18 May 2021
TradeR: Practical Deep Hierarchical Reinforcement Learning for Trade
  Execution
TradeR: Practical Deep Hierarchical Reinforcement Learning for Trade Execution
Karush Suri
Xiaolong Shi
Konstantinos Plataniotis
Y. Lawryshyn
OffRL
159
4
0
16 Feb 2021
Jointly Learning Environments and Control Policies with Projected
  Stochastic Gradient Ascent
Jointly Learning Environments and Control Policies with Projected Stochastic Gradient AscentJournal of Artificial Intelligence Research (JAIR), 2020
Adrien Bolland
Ioannis Boukas
M. Berger
D. Ernst
521
4
0
02 Jun 2020
An Application of Deep Reinforcement Learning to Algorithmic Trading
An Application of Deep Reinforcement Learning to Algorithmic TradingExpert systems with applications (ESWA), 2020
Thibaut Théate
D. Ernst
AIFin
353
209
0
07 Apr 2020
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