Alain Andres

Orcid: 0000-0002-4688-1304

According to our database1, Alain Andres authored at least 14 papers between 2021 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

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Bibliography

2025
Using offline data to speed up Reinforcement Learning in procedurally generated environments.
Neurocomputing, 2025

2024
On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution Data.
CoRR, 2024

On the Black-box Explainability of Object Detection Models for Safe and Trustworthy Industrial Applications.
CoRR, 2024

Words as Beacons: Guiding RL Agents with High-Level Language Prompts.
CoRR, 2024

Fostering Intrinsic Motivation in Reinforcement Learning with Pretrained Foundation Models.
CoRR, 2024

Surgical Task Automation Using Actor-Critic Frameworks and Self-Supervised Imitation Learning.
CoRR, 2024

Advancing towards Safe Reinforcement Learning over Sparse Environments with Out-of-Distribution Observations: Detection and Adaptation Strategies.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
Collaborative training of heterogeneous reinforcement learning agents in environments with sparse rewards: what and when to share?
Neural Comput. Appl., August, 2023

Using Offline Data to Speed-up Reinforcement Learning in Procedurally Generated Environments.
CoRR, 2023

Evolutionary Multi-Objective Quantization of Randomization-Based Neural Networks.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Enhanced Generalization Through Prioritization and Diversity in Self-Imitation Reinforcement Learning Over Procedural Environments with Sparse Rewards.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

2022
Towards Improving Exploration in Self-Imitation Learning using Intrinsic Motivation.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

An Evaluation Study of Intrinsic Motivation Techniques Applied to Reinforcement Learning over Hard Exploration Environments.
Proceedings of the Machine Learning and Knowledge Extraction, 2022

2021
Collaborative Exploration and Reinforcement Learning between Heterogeneously Skilled Agents in Environments with Sparse Rewards.
Proceedings of the International Joint Conference on Neural Networks, 2021


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