Carlo D'Eramo

According to our database, Carlo D'Eramo authored at least 44 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Learning to Explore in Diverse Reward Settings via Temporal-Difference-Error Maximization.

Sebastian Griesbach, Carlo D'Eramo

CoRR, June, 2025

Bridging the Performance Gap Between Target-Free and Target-Based Reinforcement Learning With Iterated Q-Learning.

Théo Vincent, Yogesh Tripathi, Tim Lukas Faust, Yaniv Oren, Jan Peters, Carlo D'Eramo

CoRR, June, 2025

Dynamic Obstacle Avoidance with Bounded Rationality Adversarial Reinforcement Learning.

Jose Luis Holgado Alvarez, Aryaman Reddi, Carlo D'Eramo

CoRR, March, 2025

Eau De <i>Q</i>-Network: Adaptive Distillation of Neural Networks in Deep Reinforcement Learning.

Théo Vincent, Tim Lukas Faust, Yogesh Tripathi, Jan Peters, Carlo D'Eramo

CoRR, March, 2025

Continual Learning Should Move Beyond Incremental Classification.

Rupert Mitchell, Antonio Alliegro, Raffaello Camoriano, Dustin Carrión-Ojeda, Antonio Carta, Georgia Chalvatzaki, Nikhil Churamani, Carlo D'Eramo, Samin Hamidi, Robin Hesse, Fabian Hinder, Roshni Kamath, Vincenzo Lomonaco, Subarnaduti Paul, Francesca Pistilli, Tinne Tuytelaars, Gido M. van de Ven, Kristian Kersting, Simone Schaub-Meyer, Martin Mundt

CoRR, February, 2025

Machine Learning with Physics Knowledge for Prediction: A Survey.

Joe Watson, Chen Song, Oliver Weeger, Theo Gruner, An Thai Le, Kay Hansel, Ahmed Hendawy, Oleg Arenz, Will Trojak, Miles D. Cranmer, Carlo D'Eramo, Fabian Bülow, Tanmay Goyal, Jan Peters, Martin W. Hoffmann

Trans. Mach. Learn. Res., 2025

Iterated <i>Q</i>-Network: Beyond One-Step Bellman Updates in Deep Reinforcement Learning.

Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo

Trans. Mach. Learn. Res., 2025

Real-World Testing Matters in Reinforcement Learning for Education.

Anna Riedmann, Carlo D'Eramo, Birgit Lugrin

Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning.

Théo Vincent, Fabian Wahren, Jan Peters, Boris Belousov, Carlo D'Eramo

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

On the Benefit of Optimal Transport for Curriculum Reinforcement Learning.

Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

IEEE Trans. Pattern Anal. Mach. Intell., November, 2024

A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search.

Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen

J. Artif. Intell. Res., 2024

Deterministic Exploration via Stationary Bellman Error Maximization.

Sebastian Griesbach, Carlo D'Eramo

CoRR, 2024

Iterated Q-Network: Beyond the One-Step Bellman Operator.

Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo

CoRR, 2024

Cyclicity-Regularized Coordination Graphs.

Oliver Järnefelt, Mahdi Kallel, Carlo D'Eramo

RLJ, 2024

Uli-RL: A Real-World Deep Reinforcement Learning Pedagogical Agent for Children.

Anna Riedmann, Julia Götz, Carlo D'Eramo, Birgit Lugrin

Proceedings of the KI 2024: Advances in Artificial Intelligence, 2024

Contact Energy Based Hindsight Experience Prioritization.

Erdi Sayar, Zhenshan Bing, Carlo D'Eramo, Ozgur S. Oguz, Alois Knoll

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Domain Randomization via Entropy Maximization.

Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula.

Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Augmented Bayesian Policy Search.

Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts.

Ahmed Hendawy, Jan Peters, Carlo D'Eramo

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Parameterized Projected Bellman Operator.

Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Composable energy policies for reactive motion generation and reinforcement learning.

Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters

Int. J. Robotics Res., September, 2023

Monte-Carlo tree search with uncertainty propagation via optimal transport.

Tuan Dam, Pascal Stenger, Lukas Schneider, Joni Pajarinen, Carlo D'Eramo, Odalric-Ambrym Maillard

CoRR, 2023

2022

Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning.

Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Algorithms, 2022

Prioritized Sampling with Intrinsic Motivation in Multi-Task Reinforcement Learning.

Carlo D'Eramo, Georgia Chalvatzaki

Proceedings of the International Joint Conference on Neural Networks, 2022

Curriculum Reinforcement Learning via Constrained Optimal Transport.

Pascal Klink, Haoyi Yang, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Proceedings of the International Conference on Machine Learning, 2022

Boosted Curriculum Reinforcement Learning.

Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning.

Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen

J. Mach. Learn. Res., 2021

MushroomRL: Simplifying Reinforcement Learning Research.

Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters

J. Mach. Learn. Res., 2021

Gaussian Approximation for Bias Reduction in Q-Learning.

Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli

J. Mach. Learn. Res., 2021

Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning.

Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, Carlo D'Eramo, Aaron M. Dollar, Jan Peters

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Convex Regularization in Monte-Carlo Tree Search.

Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Multi-Channel Interactive Reinforcement Learning for Sequential Tasks.

Dorothea Koert, Maximilian Kircher, Vildan Salikutluk, Carlo D'Eramo, Jan Peters

Frontiers Robotics AI, 2020

Deep Reinforcement Learning with Weighted Q-Learning.

Andrea Cini, Carlo D'Eramo, Jan Peters, Cesare Alippi

CoRR, 2020

Self-Paced Deep Reinforcement Learning.

Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generalized Mean Estimation in Monte-Carlo Tree Search.

Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Sharing Knowledge in Multi-Task Deep Reinforcement Learning.

Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

On the exploitation of uncertainty to improve Bellman updates and exploration in Reinforcement Learning.

Carlo D'Eramo

PhD thesis, 2019

Exploration Driven by an Optimistic Bellman Equation.

Samuele Tosatto, Carlo D'Eramo, Joni Pajarinen, Marcello Restelli, Jan Peters

Proceedings of the International Joint Conference on Neural Networks, 2019

Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning.

Carlo D'Eramo, Andrea Cini, Marcello Restelli

Proceedings of the International Joint Conference on Neural Networks, 2019

2017

Exploiting structure and uncertainty of Bellman updates in Markov decision processes.

Davide Tateo, Carlo D'Eramo, Alessandro Nuara, Marcello Restelli, Andrea Bonarini

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Boosted Fitted Q-Iteration.

Samuele Tosatto, Matteo Pirotta, Carlo D'Eramo, Marcello Restelli

Proceedings of the 34th International Conference on Machine Learning, 2017

Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems.

Carlo D'Eramo, Alessandro Nuara, Matteo Pirotta, Marcello Restelli

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Estimating Maximum Expected Value through Gaussian Approximation.

Carlo D'Eramo, Marcello Restelli, Alessandro Nuara

Proceedings of the 33nd International Conference on Machine Learning, 2016