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Miguel Suau
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Year
Influence-aware Memory Architectures for Deep Reinforcement Learning in POMDPs
M Suau, J He, E Congeduti, RAN Starre, A Czechowski, FA Oliehoek
Neural Computing and Applications 2022, 2019
14*2019
Diseño y construcción de una mini–turbina eólica
M Suau de Castro
Universidad Politécnica de Madrid, 2014
112014
Influence-Augmented Online Planning for Complex Environments
J He, M Suau, F Oliehoek
NeurIPS 2020, 2020
92020
Offline Contextual Bandits for Wireless Network Optimization
M Suau, A Agapitos, D Lynch, D Farrell, M Zhou, A Milenovic
NeurIPS 2021, Offline RL workshop, 2021
42021
Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems
M Suau, J He, MTJ Spaan, FA Oliehoek
ICML 2022, 2022
32022
Speeding up deep reinforcement learning through influence-augmented local simulators
M Suau, J He, MTJ Spaan, FA Oliehoek
AAMAS 2022, 2022
22022
Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL
M Suau, MTJ Spaan, FA Oliehoek
arXiv preprint arXiv:2306.02419, 2023
12023
Distributed Influence-Augmented Local Simulators for Parallel MARL in Large Networked Systems
M Suau, J He, MM Çelikok, MTJ Spaan, FA Oliehoek
NeurIPS 2022, 2022
12022
Online Planning in POMDPs with Self-Improving Simulators
J He, M Suau, H Baier, M Kaisers, FA Oliehoek
IJCAI 2022, 2022
12022
Learning What to Attend to: Using Bisimulation Metrics to Explore and Improve Upon What a Deep Reinforcement Learning Agent Learns⋆
N Albers, M Suau, FA Oliehoek
TU Delft, 2020
12020
Leveraging Factored State Representations for Enhanced Efficiency in Reinforcement Learning
M Suau
2024
Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in Reinforcement Learning
M Suau, MTJ Spaan, FA Oliehoek
2023
AboutInfluence'
FA Oliehoek, E Congeduti, A Czechowski, J He, A Mey, RAN Starre, ...
2022
Using Bisimulation Metrics to Analyze and Evaluate Latent State Representations
N Albers, M Suau, FA Oliehoek
BNAIC 2021, 2021
2021
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Articles 1–14