Carlo D'Eramo

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 48

Top Topics

Monte Carlo Search

Markov Decision Process

Probabilistic Interpretation

Reinforcement Learning

Top Venues

Publications

Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo
Parameterized Projected Bellman Operator. AAAI (2024)
Théo Vincent, Fabian Wahren, Jan Peters, Boris Belousov, Carlo D'Eramo
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning. CoRR (2024)
Erdi Sayar, Zhenshan Bing, Carlo D'Eramo, Ozgur S. Oguz, Alois Knoll
Contact Energy Based Hindsight Experience Prioritization. ICRA (2024)
Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo
Augmented Bayesian Policy Search. ICLR (2024)
Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo
Augmented Bayesian Policy Search. CoRR (2024)
Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula. ICLR (2024)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. CoRR (2024)
Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki
Domain Randomization via Entropy Maximization. ICLR (2024)
Ahmed Hendawy, Jan Peters, Carlo D'Eramo
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts. ICLR (2024)
Théo Vincent, Daniel Palenicek, Boris Belousov, Jan Peters, Carlo D'Eramo
Iterated Q-Network: Beyond the One-Step Bellman Operator. CoRR (2024)
Ahmed Hendawy, Jan Peters, Carlo D'Eramo
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts. CoRR (2023)
Tuan Dam, Pascal Stenger, Lukas Schneider, Joni Pajarinen, Carlo D'Eramo, Odalric-Ambrym Maillard
Monte-Carlo tree search with uncertainty propagation via optimal transport. CoRR (2023)
Gabriele Tiboni, Pascal Klink, Jan Peters, Tatiana Tommasi, Carlo D'Eramo, Georgia Chalvatzaki
Domain Randomization via Entropy Maximization. CoRR (2023)
Erdi Sayar, Zhenshan Bing, Carlo D'Eramo, Ozgur S. Oguz, Alois Knoll
Contact Energy Based Hindsight Experience Prioritization. CoRR (2023)
Théo Vincent, Alberto Maria Metelli, Boris Belousov, Jan Peters, Marcello Restelli, Carlo D'Eramo
Parameterized Projected Bellman Operator. CoRR (2023)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
On the Benefit of Optimal Transport for Curriculum Reinforcement Learning. CoRR (2023)
Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters
Composable energy policies for reactive motion generation and reinforcement learning. Int. J. Robotics Res. 42 (10) (2023)
Aryaman Reddi, Maximilian Tölle, Jan Peters, Georgia Chalvatzaki, Carlo D'Eramo
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula. CoRR (2023)
Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning. Algorithms 15 (3) (2022)
Carlo D'Eramo, Georgia Chalvatzaki
Prioritized Sampling with Intrinsic Motivation in Multi-Task Reinforcement Learning. IJCNN (2022)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Boosted Curriculum Reinforcement Learning. ICLR (2022)
Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search. CoRR (2022)
Pascal Klink, Haoyi Yang, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Curriculum Reinforcement Learning via Constrained Optimal Transport. ICML (2022)
Carlo D'Eramo, Andrea Cini, Alessandro Nuara, Matteo Pirotta, Cesare Alippi, Jan Peters, Marcello Restelli
Gaussian Approximation for Bias Reduction in Q-Learning. J. Mach. Learn. Res. 22 (2021)
Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, Carlo D'Eramo, Aaron M. Dollar, Jan Peters
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning. CoRR (2021)
Julen Urain, Puze Liu, Anqi Li, Carlo D'Eramo, Jan Peters
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning. Robotics: Science and Systems (2021)
Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. J. Mach. Learn. Res. 22 (2021)
Julen Urain, Anqi Li, Puze Liu, Carlo D'Eramo, Jan Peters
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning. CoRR (2021)
Andrew S. Morgan, Daljeet Nandha, Georgia Chalvatzaki, Carlo D'Eramo, Aaron M. Dollar, Jan Peters
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning. ICRA (2021)
Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning. CoRR (2021)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
MushroomRL: Simplifying Reinforcement Learning Research. J. Mach. Learn. Res. 22 (2021)
Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Convex Regularization in Monte-Carlo Tree Search. ICML (2021)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
MushroomRL: Simplifying Reinforcement Learning Research. CoRR (2020)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Self-Paced Deep Reinforcement Learning. CoRR (2020)
Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Convex Regularization in Monte-Carlo Tree Search. CoRR (2020)
Andrea Cini, Carlo D'Eramo, Jan Peters, Cesare Alippi
Deep Reinforcement Learning with Weighted Q-Learning. CoRR (2020)
Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Generalized Mean Estimation in Monte-Carlo Tree Search. IJCAI (2020)
Simone Parisi, Davide Tateo, Maximilian Hensel, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Long-Term Visitation Value for Deep Exploration in Sparse Reward Reinforcement Learning. CoRR (2020)
Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters
Sharing Knowledge in Multi-Task Deep Reinforcement Learning. ICLR (2020)
Dorothea Koert, Maximilian Kircher, Vildan Salikutluk, Carlo D'Eramo, Jan Peters
Multi-Channel Interactive Reinforcement Learning for Sequential Tasks. Frontiers Robotics AI 7 (2020)
Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Self-Paced Deep Reinforcement Learning. NeurIPS (2020)
Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen
Generalized Mean Estimation in Monte-Carlo Tree Search. CoRR (2019)
Samuele Tosatto, Carlo D'Eramo, Joni Pajarinen, Marcello Restelli, Jan Peters
Exploration Driven by an Optimistic Bellman Equation. IJCNN (2019)
Carlo D'Eramo, Andrea Cini, Marcello Restelli
Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning. IJCNN (2019)
Carlo D'Eramo, Alessandro Nuara, Matteo Pirotta, Marcello Restelli
Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems. AAAI (2017)
Davide Tateo, Carlo D'Eramo, Alessandro Nuara, Marcello Restelli, Andrea Bonarini
Exploiting structure and uncertainty of Bellman updates in Markov decision processes. SSCI (2017)
Samuele Tosatto, Matteo Pirotta, Carlo D'Eramo, Marcello Restelli
Boosted Fitted Q-Iteration. ICML (2017)
Carlo D'Eramo, Marcello Restelli, Alessandro Nuara
Estimating Maximum Expected Value through Gaussian Approximation. ICML (2016)