Damien Ernst

Orcid: 0000-0002-3035-8260

Affiliations:
  • University of Liège, Belgium


According to our database1, Damien Ernst authored at least 129 papers between 2000 and 2024.

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Bibliography

2024
Exploiting the Flexibility Potential of Water Distribution Networks: A Pilot Project in Belgium.
IEEE Trans. Smart Grid, January, 2024

Behind the Myth of Exploration in Policy Gradients.
CoRR, 2024

Optimal Control of Renewable Energy Communities subject to Network Peak Fees with Model Predictive Control and Reinforcement Learning Algorithms.
CoRR, 2024

Comprehensive Review on Static and Dynamic Distribution Network Reconfiguration Methodologies.
IEEE Access, 2024

2023
Warming up recurrent neural networks to maximise reachable multistability greatly improves learning.
Neural Networks, September, 2023

Risk-Sensitive Policy with Distributional Reinforcement Learning.
Algorithms, July, 2023

Distributional reinforcement learning with unconstrained monotonic neural networks.
Neurocomputing, 2023

Informed POMDP: Leveraging Additional Information in Model-Based RL.
CoRR, 2023

Spike-based computation using classical recurrent neural networks.
CoRR, 2023

Policy Gradient Algorithms Implicitly Optimize by Continuation.
CoRR, 2023

Multi-objective near-optimal necessary conditions for multi-sectoral planning.
CoRR, 2023

IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Impacts of spatial and temporal resolutions on the near-optimal spaces of energy system optimisation models.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2023

2022
Recurrent networks, hidden states and beliefs in partially observable environments.
Trans. Mach. Learn. Res., 2022

Parallax Inference for Robust Temporal Monocular Depth Estimation in Unstructured Environments.
Sensors, 2022

Siting renewable power generation assets with combinatorial optimisation.
Optim. Lett., 2022

GBOML: Graph-Based Optimization Modeling Language.
J. Open Source Softw., 2022

Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent.
J. Artif. Intell. Res., 2022

Value-based CTDE Methods in Symmetric Two-team Markov Game: from Cooperation to Team Competition.
CoRR, 2022

Optimal Connection Phase Selection of Residential Distributed Energy Resources and its Impact on Aggregated Demand.
CoRR, 2022

Churn prediction in online gambling.
CoRR, 2022

Financial Optimization of Renewable Energy Communities Through Optimal Allocation of Locally Generated Electricity.
IEEE Access, 2022

2021
Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education.
Softw. Impacts, 2021

A deep reinforcement learning framework for continuous intraday market bidding.
Mach. Learn., 2021

An application of deep reinforcement learning to algorithmic trading.
Expert Syst. Appl., 2021

Computing Necessary Conditions for Near-Optimality in Capacity Expansion Planning Problems.
CoRR, 2021

Warming-up recurrent neural networks to maximize reachable multi-stability greatly improves learning.
CoRR, 2021

M4Depth: A motion-based approach for monocular depth estimation on video sequences.
CoRR, 2021

Model Reduction in Capacity Expansion Planning Problems via Renewable Generation Site Selection.
CoRR, 2021

Gym-ANM: Reinforcement Learning Environments for Active Network Management Tasks in Electricity Distribution Systems.
CoRR, 2021

Remote Renewable Hubs For Carbon-Neutral Synthetic Fuel Production.
CoRR, 2021

Reconstruction of Low-Voltage Networks with Limited Observability.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2021

Sparse Training Theory for Scalable and Efficient Agents.
Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020
QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning.
CoRR, 2020

Assessing the Economic Value of Renewable Resource Complementarity for Power Systems: an ENTSO-E Study.
CoRR, 2020

Allocation of locally generated electricity in renewable energy communities.
CoRR, 2020

An Artificial Intelligence Solution for Electricity Procurement in Forward Markets.
CoRR, 2020

A bio-inspired bistable recurrent cell allows for long-lasting memory.
CoRR, 2020

Learning optimal environments using projected stochastic gradient ascent.
CoRR, 2020

On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract).
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability.
J. Artif. Intell. Res., 2019

Blockchain: A Novel Approach for the Consensus Algorithm Using Condorcet Voting Procedure.
Proceedings of the IEEE International Conference on Decentralized Applications and Infrastructures, 2019

2018
Pulse-Based Control Using Koopman Operator Under Parametric Uncertainty.
IEEE Trans. Autom. Control., 2018

Introducing Neuromodulation in Deep Neural Networks to Learn Adaptive Behaviours.
CoRR, 2018

Complementarity Assessment of South Greenland Katabatic Flows and West Europe Wind Regimes.
CoRR, 2018

Critical Time Windows for Renewable Resource Complementarity Assessment.
CoRR, 2018

Optimal control formulation of pulse-based control using Koopman operator.
Autom., 2018

Effect of voltage constraints on the exchange of flexibility services in distribution networks.
Proceedings of the 2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2018

2017
A biased random key genetic algorithm applied to the electric distribution network reconfiguration problem.
J. Heuristics, 2017

On overfitting and asymptotic bias in batch reinforcement learning with partial observability.
CoRR, 2017

An Optimal Control Formulation of Pulse-Based Control Using Koopman Operator.
CoRR, 2017

An App-based Algorithmic Approach for Harvesting Local and Renewable Energy using Electric Vehicles.
Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017

Approximate Bayes Optimal Policy Search using Neural Networks.
Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017

2016
Active Management of Low-Voltage Networks for Mitigating Overvoltages Due to Photovoltaic Units.
IEEE Trans. Smart Grid, 2016

Direct control service from residential heat pump aggregation with specified payback.
Proceedings of the Power Systems Computation Conference, 2016

A Gaussian mixture approach to model stochastic processes in power systems.
Proceedings of the Power Systems Computation Conference, 2016

Agent-based analysis of dynamic access ranges to the distribution network.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference Europe, 2016

Decision Making from Confidence Measurement on the Reward Growth using Supervised Learning - A Study Intended for Large-scale Video Games.
Proceedings of the 8th International Conference on Agents and Artificial Intelligence (ICAART 2016), 2016

2015
Reinforcement Learning of Heuristic EV Fleet Charging in a Day-Ahead Electricity Market.
IEEE Trans. Smart Grid, 2015

Artificial Intelligence in Video Games: Towards a Unified Framework.
Int. J. Comput. Games Technol., 2015

Sequential decision-making approach for quadrangular mesh generation.
Eng. Comput., 2015

How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies.
CoRR, 2015

Benchmarking for Bayesian Reinforcement Learning.
CoRR, 2015

Imitative Learning for Online Planning in Microgrids.
Proceedings of the Data Analytics for Renewable Energy Integration, 2015

2014
Active network management for electrical distribution systems: problem formulation and benchmark.
CoRR, 2014

A quantitative analysis of the effect of flexible loads on reserve markets.
Proceedings of the 2014 Power Systems Computation Conference, 2014

Relaxations for multi-period optimal power flow problems with discrete decision variables.
Proceedings of the 2014 Power Systems Computation Conference, 2014

Simple Connectome Inference from Partial Correlation Statistics in Calcium Imaging.
Proceedings of the Neural Connectomics Workshop at ECML 2014, 2014

Lipschitz robust control from off-policy trajectories.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Using approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device.
Proceedings of the 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2014

2013
Monte Carlo Search Algorithm Discovery for Single-Player Games.
IEEE Trans. Comput. Intell. AI Games, 2013

Min Max Generalization for Deterministic Batch Mode Reinforcement Learning: Relaxation Schemes.
SIAM J. Control. Optim., 2013

Stratégies d'échantillonnage pour l'apprentissage par renforcement batch.
Rev. d'Intelligence Artif., 2013

Optimal discovery with probabilistic expert advice: finite time analysis and macroscopic optimality.
J. Mach. Learn. Res., 2013

Scenario Trees and Policy Selection for Multistage Stochastic Programming Using Machine Learning.
INFORMS J. Comput., 2013

Toggling a Genetic Switch Using Reinforcement Learning
CoRR, 2013

Outbound SPIT filter with optimal performance guarantees.
Comput. Networks, 2013

Batch mode reinforcement learning based on the synthesis of artificial trajectories.
Ann. Oper. Res., 2013

An efficient algorithm for the provision of a day-ahead modulation service by a load aggregator.
Proceedings of the 4th IEEE PES Innovative Smart Grid Technologies Europe, 2013

On periodic reference tracking using batch-mode reinforcement learning with application to gene regulatory network control.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Optimized look-ahead trees: Extensions to large and continuous action spaces.
Proceedings of the 2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2013

2012
Optimized Look-Ahead Tree Policies: A Bridge Between Look-Ahead Tree Policies and Direct Policy Search
CoRR, 2012

Monte Carlo Search Algorithm Discovery for One Player Games
CoRR, 2012

The Global Grid
CoRR, 2012

Contextual Multi-armed Bandits for the Prevention of Spam in VoIP Networks
CoRR, 2012

Cooperative frequency control with a multi-terminal high-voltage DC network.
Autom., 2012

Contextual multi-armed bandits for web server defense.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Meta-learning of Exploration/Exploitation Strategies: The Multi-armed Bandit Case.
Proceedings of the Agents and Artificial Intelligence - 4th International Conference, 2012

Learning to Play K-armed Bandit Problems.
Proceedings of the ICAART 2012 - Proceedings of the 4th International Conference on Agents and Artificial Intelligence, Volume 1, 2012

Learning Exploration/Exploitation Strategies for Single Trajectory Reinforcement Learning.
Proceedings of the Tenth European Workshop on Reinforcement Learning, 2012

Policy Search in a Space of Simple Closed-form Formulas: Towards Interpretability of Reinforcement Learning.
Proceedings of the Discovery Science - 15th International Conference, 2012

Comparison of different selection strategies in Monte-Carlo Tree Search for the game of Tron.
Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012

Imitative learning for real-time strategy games.
Proceedings of the 2012 IEEE Conference on Computational Intelligence and Games, 2012

Optimal discovery with probabilistic expert advice.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

SPRT for SPIT: Using the Sequential Probability Ratio Test for Spam in VoIP Prevention.
Proceedings of the Dependable Networks and Services, 2012

2011
Cross-Entropy Optimization of Control Policies With Adaptive Basis Functions.
IEEE Trans. Syst. Man Cybern. Part B, 2011

Estimation Monte Carlo sans modèle de politiques de décision.
Rev. d'Intelligence Artif., 2011

Model predictive control of HVDC power flow to improve transient stability in power systems.
Proceedings of the IEEE Second International Conference on Smart Grid Communications, 2011

Optimal Sample Selection for Batch-mode Reinforcement Learning.
Proceedings of the ICAART 2011 - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence, Volume 1, 2011

Optimized Look-ahead Tree Search Policies.
Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

Automatic Discovery of Ranking Formulas for Playing with Multi-armed Bandits.
Proceedings of the Recent Advances in Reinforcement Learning - 9th European Workshop, 2011

Active exploration by searching for experiments that falsify the computed control policy.
Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming And Reinforcement Learning, 2011

Approximate reinforcement learning: An overview.
Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming And Reinforcement Learning, 2011

2010
Model-Free Monte Carlo-like Policy Evaluation.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Approximate dynamic programming with a fuzzy parameterization.
Autom., 2010

Upper Confidence Bound Based Decision Making Strategies and Dynamic Spectrum Access.
Proceedings of IEEE International Conference on Communications, 2010

Towards Min Max Generalization in Reinforcement Learning.
Proceedings of the Agents and Artificial Intelligence - Second International Conference, 2010

A Cautious Approach to Generalization in Reinforcement Learning.
Proceedings of the ICAART 2010 - Proceedings of the International Conference on Agents and Artificial Intelligence, Volume 1, 2010

Online least-squares policy iteration for reinforcement learning control.
Proceedings of the American Control Conference, 2010

2009
Reinforcement Learning Versus Model Predictive Control: A Comparison on a Power System Problem.
IEEE Trans. Syst. Man Cybern. Part B, 2009

Bounds for Multistage Stochastic Programs Using Supervised Learning Strategies.
Proceedings of the Stochastic Algorithms: Foundations and Applications, 2009

Decentralized Reactive Power Dispatch for a Time-Varying Multi-TSO System.
Proceedings of the 42st Hawaii International International Conference on Systems Science (HICSS-42 2009), 2009

Inferring bounds on the performance of a control policy from a sample of trajectories.
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

Planning under uncertainty, ensembles of disturbance trees and kernelized discrete action spaces.
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

Policy search with cross-entropy optimization of basis functions.
Proceedings of the IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, 2009

2008
Consistency of fuzzy model-based reinforcement learning.
Proceedings of the FUZZ-IEEE 2008, 2008

Lazy Planning under Uncertainty by Optimizing Decisions on an Ensemble of Incomplete Disturbance Trees.
Proceedings of the Recent Advances in Reinforcement Learning, 8th European Workshop, 2008

2007
Estimation of rotor angles of synchronous machines using artificial neural networks and local PMU-based quantities.
Neurocomputing, 2007

Fuzzy Approximation for Convergent Model-Based Reinforcement Learning.
Proceedings of the FUZZ-IEEE 2007, 2007

Continuous-State Reinforcement Learning with Fuzzy Approximation.
Proceedings of the Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning, 2007

2006
Extremely randomized trees.
Mach. Learn., 2006

Reinforcement Learning with Raw Image Pixels as Input State.
Proceedings of the Advances in Machine Vision, 2006

Clinical data based optimal STI strategies for HIV: a reinforcement learning approach.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006

2005
Tree-Based Batch Mode Reinforcement Learning.
J. Mach. Learn. Res., 2005

2003
Near Optimal Closed-Loop Control. Application to Electric Power Systems.
PhD thesis, 2003

Iteratively Extending Time Horizon Reinforcement Learning.
Proceedings of the Machine Learning: ECML 2003, 2003

2001
A control strategy for controllable series capacitor in electric power systems.
Autom., 2001

Reinforcement learning applied to power system oscillations damping.
Proceedings of the 40th IEEE Conference on Decision and Control, 2001

2000
Application of Reinforcement Learning to Electrical Power System Closed-Loop Emergency Control.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000


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