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06/20/2023
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL
We introduce IMP-MARL, an open-source suite of multi-agent reinforcement...
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06/20/2023
Informed POMDP: Leveraging Additional Information in Model-Based RL
In this work, we generalize the problem of learning through interaction ...
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06/06/2023
Spike-based computation using classical recurrent neural networks
Spiking neural networks are a type of artificial neural networks in whic...
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05/11/2023
Policy Gradient Algorithms Implicitly Optimize by Continuation
Direct policy optimization in reinforcement learning is usually solved w...
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12/30/2022
Risk-Sensitive Policy with Distributional Reinforcement Learning
Classical reinforcement learning (RL) techniques are generally concerned...
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11/21/2022
Value-based CTDE Methods in Symmetric Two-team Markov Game: from Cooperation to Team Competition
In this paper, we identify the best learning scenario to train a team of...
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08/06/2022
Recurrent networks, hidden states and beliefs in partially observable environments
Reinforcement learning aims to learn optimal policies from interaction w...
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07/08/2022
Optimal Connection Phase Selection of Residential Distributed Energy Resources and its Impact on Aggregated Demand
The recent major increase in decentralized energy resources (DERs) such ...
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01/07/2022
Churn prediction in online gambling
In business retention, churn prevention has always been a major concern....
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06/06/2021
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks
The distributional reinforcement learning (RL) approach advocates for re...
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06/02/2021
Warming-up recurrent neural networks to maximize reachable multi-stability greatly improves learning
Training recurrent neural networks is known to be difficult when time de...
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05/20/2021
M4Depth: A motion-based approach for monocular depth estimation on video sequences
Getting the distance to objects is crucial for autonomous vehicles. In i...
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05/18/2021
Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education
Gym-ANM is a Python package that facilitates the design of reinforcement...
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03/14/2021
Gym-ANM: Reinforcement Learning Environments for Active Network Management Tasks in Electricity Distribution Systems
Active network management (ANM) of electricity distribution networks inc...
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03/02/2021
Sparse Training Theory for Scalable and Efficient Agents
A fundamental task for artificial intelligence is learning. Deep Neural ...
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02/22/2021
Remote Renewable Hubs For Carbon-Neutral Synthetic Fuel Production
This paper studies the economics of carbon-neutral synthetic fuel produc...
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12/22/2020
QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning
This paper introduces four new algorithms that can be used for tackling ...
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09/09/2020
Allocation of locally generated electricity in renewable energy communities
This paper introduces a methodology to perform an ex-post allocation of ...
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06/10/2020
An Artificial Intelligence Solution for Electricity Procurement in Forward Markets
Retailers and major consumers of electricity generally purchase a critic...
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06/09/2020
A bio-inspired bistable recurrent cell allows for long-lasting memory
Recurrent neural networks (RNNs) provide state-of-the-art performances i...
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06/02/2020
Learning optimal environments using projected stochastic gradient ascent
In this work, we generalize the direct policy search algorithms to an al...
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04/13/2020
A Deep Reinforcement Learning Framework for Continuous Intraday Market Bidding
The large integration of variable energy resources is expected to shift ...
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04/07/2020
An Application of Deep Reinforcement Learning to Algorithmic Trading
This scientific research paper presents an innovative approach based on ...
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12/21/2018
Introducing Neuromodulation in Deep Neural Networks to Learn Adaptive Behaviours
In this paper, we propose a new deep neural network architecture, called...
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12/05/2018
Critical Time Windows for Renewable Resource Complementarity Assessment
This paper proposes a systematic framework to assess the complementarity...
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12/05/2018
Complementarity Assessment of South Greenland Katabatic Flows and West Europe Wind Regimes
Current global environmental challenges require firm, yet diverse resolu...
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09/22/2017
On overfitting and asymptotic bias in batch reinforcement learning with partial observability
This paper stands in the context of reinforcement learning with partial ...
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12/07/2015
How to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies
Using deep neural nets as function approximator for reinforcement learni...
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09/14/2015
Benchmarking for Bayesian Reinforcement Learning
In the Bayesian Reinforcement Learning (BRL) setting, agents try to maxi...
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06/30/2014
Simple connectome inference from partial correlation statistics in calcium imaging
In this work, we propose a simple yet effective solution to the problem ...
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08/23/2012
Optimized Look-Ahead Tree Policies: A Bridge Between Look-Ahead Tree Policies and Direct Policy Search
Direct policy search (DPS) and look-ahead tree (LT) policies are two wid...
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08/23/2012
Monte Carlo Search Algorithm Discovery for One Player Games
Much current research in AI and games is being devoted to Monte Carlo se...
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07/22/2012
Optimal discovery with probabilistic expert advice: finite time analysis and macroscopic optimality
We consider an original problem that arises from the issue of security a...
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07/22/2012
Meta-Learning of Exploration/Exploitation Strategies: The Multi-Armed Bandit Case
The exploration/exploitation (E/E) dilemma arises naturally in many subf...
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12/19/2011
